Lowpoly Office
-
- Demo for Lowpoly Office Stable Diffusion model.
- {"Add the following tokens to your prompts for the model to work properly: prefix" if prefix else ""}
-
-
diff --git a/spaces/12Venusssss/text_generator/app.py b/spaces/12Venusssss/text_generator/app.py deleted file mode 100644 index b695db464a5579b37758835138da381c828419f5..0000000000000000000000000000000000000000 --- a/spaces/12Venusssss/text_generator/app.py +++ /dev/null @@ -1,11 +0,0 @@ -import gradio as gr -from gradio.mix import Parallel - -myfirstvariable="My First Text Generation" -mylovelysecondvariable="Input text and submit." - -model1=gr.Interface.load("huggingface/gpt2") -model2=gr.Interface.load("huggingface/EleutherAI/gpt-j-6B") -model3=gr.Interface.load("huggingface/EleutherAI/gpt-neo-1.3B") - -gr.Parallel(model1, model2, model3 , title=myfirstvariable, description=mylovelysecondvariable).launch() \ No newline at end of file diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Aggiornamento Software Di Controllo Uniemens Individuale Recensioni e Opinioni degli Utenti sulla Versione 3.9.6.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Aggiornamento Software Di Controllo Uniemens Individuale Recensioni e Opinioni degli Utenti sulla Versione 3.9.6.md deleted file mode 100644 index 66f6b3b845122234c8f05ebce755b592d8dcd926..0000000000000000000000000000000000000000 --- a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Aggiornamento Software Di Controllo Uniemens Individuale Recensioni e Opinioni degli Utenti sulla Versione 3.9.6.md +++ /dev/null @@ -1,139 +0,0 @@ - -
Se sei un'impresa o un consulente che deve inviare le denunce mensili dei lavoratori dipendenti all'INPS, sai bene quanto sia importante avere un software di controllo affidabile e aggiornato. Il software di controllo Uniemens individuale è uno strumento gratuito e facile da usare che ti permette di verificare la correttezza formale e sostanziale dei file XML che devi trasmettere all'INPS tramite il portale UniEMens. In questo articolo ti spieghiamo cos'è il software di controllo Uniemens individuale, come si effettua l'aggiornamento alla versione 3.9.6 e quali sono i vantaggi che puoi ottenere con questo aggiornamento.
-Il software di controllo Uniemens individuale è un'applicazione Java che ti consente di effettuare i controlli preliminari sui file XML che devi inviare all'INPS tramite il portale UniEMens. Questi controlli riguardano sia la validità formale dei file XML rispetto allo schema XSD fornito dall'INPS, sia la coerenza sostanziale dei dati contenuti nei file XML rispetto alle regole di business definite dall'INPS.
-Download ☑ https://byltly.com/2uKvwe
Il software di controllo Uniemens individuale serve a evitare che i file XML che invii all'INPS siano scartati o rifiutati per motivi formali o sostanziali. In questo modo puoi risparmiare tempo e denaro, evitando di dover correggere e reinviare i file XML con il rischio di incorrere in sanzioni o ritardi nei pagamenti delle prestazioni previdenziali ai lavoratori.
-Le caratteristiche principali del software di controllo Uniemens individuale sono le seguenti:
-Per effettuare l'aggiornamento del software di controllo Uniemens individuale devi seguire alcuni semplici passaggi:
-Aggiornamento Software Di Controllo Uniemens Individuale Versione 3.9.6
-Aggiornamento Software Di Controllo Uniemens Individuale Settembre 2022
-Aggiornamento Software Di Controllo Uniemens Individuale INPS
-Aggiornamento Software Di Controllo Uniemens Individuale Download
-Aggiornamento Software Di Controllo Uniemens Individuale Manuale
-Aggiornamento Software Di Controllo Uniemens Individuale Certificato Digitale
-Aggiornamento Software Di Controllo Uniemens Individuale Servizio Caratteristiche Contributive
-Aggiornamento Software Di Controllo Uniemens Individuale Portale Inps
-Aggiornamento Software Di Controllo Uniemens Individuale Per le Aziende ed i Consulenti
-Aggiornamento Software Di Controllo Uniemens Individuale Novità della Versione
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Versione 4.0.3
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Novembre 2022
-Nuovo Software Di Controllo Uniemens Multi-piattaforma INPS
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Download
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Manuale
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Desktop e da Riga di Comando
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Microsoft Windows 10
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Microsoft Windows 8
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Microsoft Windows 7
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Linux
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Portale Inps
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Per le Aziende ed i Consulenti
-Nuovo Software Di Controllo Uniemens Multi-piattaforma Novità della Versione
-Come Aggiornare il Software Di Controllo Uniemens Individuale
-Come Scaricare il Software Di Controllo Uniemens Individuale
-Come Usare il Software Di Controllo Uniemens Individuale
-Come Installare il Software Di Controllo Uniemens Individuale
-Come Configurare il Software Di Controllo Uniemens Individuale
-Come Verificare il Software Di Controllo Uniemens Individuale
-Come Risolvere i Problemi del Software Di Controllo Uniemens Individuale
-Cos'è il Software Di Controllo Uniemens Individuale
-A Cosa Serve il Software Di Controllo Uniemens Individuale
-Quali Sono i Vantaggi del Software Di Controllo Uniemens Individuale
-Quali Sono i Requisiti del Software Di Controllo Uniemens Individuale
-Quali Sono le Funzionalità del Software Di Controllo Uniemens Individuale
-Qual è la Differenza tra il Software Di Controllo Uniemens Individuale e il Nuovo Software di controllo UniEMens Multi-piattaforma
-Dove Trovare il Software di controllo UniEMens individuale
-Dove Trovare il Nuovo software di controllo UniEMens multi-piattaforma
-Perché Aggiornare il software di controllo UniEMens individuale
-Perché Usare il nuovo software di controllo UniEMens multi-piattaforma
-Guida al software di controllo UniEMens individuale
-Guida al nuovo software di controllo UniEMens multi-piattaforma
-Recensioni sul software di controllo UniEMens individuale
-Recensioni sul nuovo software di controllo UniEMens multi-piattaforma
-Domande frequenti sul software di controllo UniEMens individuale
-Domande frequenti sul nuovo software di controllo UniEMens multi-piattaforma
-Supporto tecnico per il software di controllo UniEMens individuale
-Supporto tecnico per il nuovo software di controllo UniEMens multi-piattaforma
-Video tutorial sul software di controllo UniEMens individuale
-Video tutorial sul nuovo software di controllo UniEMens multi-piattaforma
Per poter aggiornare il software di controllo Uniemens individuale devi avere i seguenti requisiti:
-La versione 3.9.6 del software di controllo Uniemens individuale è stata rilasciata dall'INPS nel settembre 2022 e presenta le seguenti novità:
-Per scaricare e installare la versione 3.9.6 del software di controllo Uniemens individuale devi seguire questi passaggi:
-Per utilizzare la versione 3.9.6 del software di controllo Uniemens individuale devi seguire questi passaggi:
-L'aggiornamento del software di controllo Uniemens individuale alla versione 3.9.6 ti offre diversi vantaggi:
-Con l'aggiornamento del software di controllo Uniemens individuale alla versione 3.9.6 puoi essere sicuro di inviare all'INPS dei file XML conformi alle ultime normative vigenti in materia di previdenza sociale. In questo modo puoi evitare di incorrere in sanzioni o contestazioni da parte dell'INPS per aver inviato dei file XML non aggiornati o non corretti.
-Con l'aggiornamento del software di controllo Uniemens individuale alla versione 3.9.6 puoi beneficiare di una migliore qualità e velocità dei controlli sui file XML che devi inviare all'INPS. Il software è infatti in grado di effettuare i controlli in modo più accurato e rapido, grazie all'ottimizzazione delle regole di business e all'implementazione delle ultime tecnologie informatiche.
-Con l'aggiornamento del software di controllo Uniemens individuale alla versione 3.9.6 puoi ridurre il rischio di commettere errori o omissioni nei file XML che devi inviare all'INPS. Il software infatti ti fornisce un report dettagliato degli esiti dei controlli, evidenziando gli eventuali errori o anomalie rilevati e consentendoti di correggerli manualmente direttamente sul file XML. In questo modo puoi evitare di inviare all'INPS dei file XML errati o incompleti, che potrebbero causarti delle sanzioni o dei ritardi nei pagamenti delle prestazioni previdenziali ai lavoratori.
-In conclusione, il software di controllo Uniemens individuale è uno strumento indispensabile per le imprese e i consulenti che devono inviare le denunce mensili dei lavoratori dipendenti all'INPS tramite il portale UniEMens. L'aggiornamento del software alla versione 3.9.6 ti offre numerosi vantaggi in termini di sicurezza, qualità, velocità e risparmio. Ti consigliamo quindi di scaricare e installare la versione 3.9.6 del software di controllo Uniemens individuale il prima possibile e di utilizzarla per verificare la correttezza dei file XML che devi inviare all'INPS.
-Qui di seguito trovi alcune domande frequenti sul software di controllo Uniemens individuale e le relative risposte:
-Domanda | Risposta |
Cos'è UniEMens? | UniEMens è il portale web dell'INPS che consente alle imprese e ai consulenti di inviare le denunce mensili dei lavoratori dipendenti in formato XML. |
Cos'è lo schema XSD? | Lo schema XSD è il documento che definisce la struttura formale dei file XML che devono essere inviati al portale UniEMens. |
Cos'è una regola di business? | Una regola di business è una condizione che deve essere rispettata dai dati contenuti nei file XML che devono essere inviati al portale UniEMens. |
Come si aggiorna il software di controllo Uniemens individuale? | Per aggiornare il software di controllo Uniemens individuale bisogna scaricare e installare la versione più recente rilasciata dall'INPS sul sito web www.inps.it. |
Come si contatta l'assistenza tecnica dell'INPS? | Per contattare l'assistenza tecnica dell'INPS bisogna chiamare il numero verde 803164 oppure scrivere una mail a assistenzatecnica@inps.it. |
اگر شما هم جزو آن دسته از افرادی هستید که علاقهمند به صدا و موسیقی هستید، حتما با اصطلاح اکولایزر آشنا هستید. اما آیا دقیقا میدانید که اکولایزر چیست و چه کاربردهایی دارد؟ در این مقاله قصد داریم به شما تعریف و مفهوم اکولایزر را بگوییم، انواع مختلف آن را معرفی کنیم و کاربردهای آن را در صنعت صوتی و موسیقی برشمریم. همچنین به شما بهترین اکولایزرهای صوتی برای ویندوز 10 در سال 2023 را معرفی خواهیم کرد. پس با ما همراه باشید.
-اکولایزر یک نوع فیلتر صوتی است که با استفاده از آن میتوان سطح فرکانسهای مختلف در یک سیگنال صوتی را تغییر داد. به عبارت دیگر، با استفاده از اکولای
زر اکولایزر میتوانید صدای خروجی را به دلخواه خود شکل دهید. برای مثال، میتوانید باس را تقویت کنید، تربل را کاهش دهید، میانصدا را افزایش دهید و غیره. اکولایزر به شما امکان میدهد که صدای خود را با توجه به نوع موسیقی، محیط، سلیقه و هدف خود تنظیم کنید.
-Download File ❤ https://jinyurl.com/2uNUzT
اکولایزرها بر اساس شکل موج و تعداد باندهایی که در آنها قابل تغییر هستند، به چند نوع تقسیمبندی میشوند. باند یک بازه فرکانسی است که در آن میتوانید سطح صدا را افزایش یا کاهش دهید. برخی از انواع اکولایزرها عبارتند از:
-اکولایزرهای گرافیکی نوعی اکولایزر هستند که در آنها تعداد باندها ثابت است و شما فقط میتوانید سطح هر باند را با استفاده از یک کشویی یا یک دکمه تغییر دهید. این نوع اکولایزر به شما اجازه نمیدهد که فرکانس و عرض هر باند را تغییر دهید. معمولا این نوع اکولایزر دارای 5، 7، 10، 15 یا 31 باند هستند. این نوع اکولایزر به خاطر سادگی و راحتی استفاده از آن در بسیاری از دستگاههای صوتی مانند پخش کنندههای MP3، ست تاپ باکسها، تلویزیونها و غیره استفاده میشود.
-دانلود رایگان 50 اکولایزر حرکتی آماده افترافکت
-با بهترین اکولایزرهای صوتی برای ویندوز 10 آشنا شوید
-ایجاد اکولایزر موزیک برای اینستاگرام و روش های ساخت آن
-اکولایزر چیست؟ هر آنچه باید در این رابطه بدانید
-Viper4Windows یک اکوالیزر منبع باز برای ویندوز 10
-نحوه تنظیم اکولایزر در سامسونگ گلکسی S21
-معرفی نرمافزار Equalizer APO برای تغییر صدا در ویندوز
-آموزش ساخت اکولایزر سه بعدی با نرمافزار Adobe After Effects
-مقایسه اکولایزرهای پارامتریک و گرافیک در صنعت صوت
-دانلود پلاگین FabFilter Pro-Q 3 برای اکولایز کردن صدا
-راهنمای خرید بهترین اکولایزر خودرو در بازار
-تفاوت اکولایزر و کمپرسور در پروسه میکس و مسترینگ
-نحوه استفاده از اپلیکیشن Equalizer FX برای تقویت صدا در اندروید
-دانلود پروژه آماده افترافکت Audio Spectrum Music Visualizer
-آشنایی با ویژگیها و تنظیمات اکولایزر Spotify
-نحوه ساخت اکولایزر حجم دار با نور LED
-دانلود نسخه جدید نرمافزار Equalizer Pro برای ویندوز 10
-آموزش تنظیم صحیح اکولایزر بلندگوها و هدفونها
-دانلود رایگان پلاگین TDR Nova برای اکولایز دینامیک صدا
-معرفی بهترین اپلیکیشنهای اکولایزر برای iOS
اکولایزرهای پارامتریک نوعی اکولایزر هستند که در آنها شما میتوانید علاوه بر سطح هر باند، فرکانس و عرض آن را نیز تغییر دهید. فرکانس نشاندهنده محل قرارگیری باند در بازه فرکانس صدا است و عرض نشاندهنده تاثیر باند بر فرکانسهای نزد
کی به آن میگویند. این نوع اکولایزر به شما امکان میدهد که با دقت بیشتری صدای خود را تنظیم کنید. معمولا این نوع اکولایزر دارای 3، 4 یا 6 باند هستند. این نوع اکولایزر در بسیاری از نرمافزارها و دستگاههای حرفهای صوتی مانند میکسرها، آمپلیفایرها، استودیوها و غیره استفاده میشود.
-اکولایزرهای شلف نوعی اکولایزر هستند که در آنها فقط دو باند وجود دارد: یک باند برای فرکانسهای پایین (باس) و یک باند برای فرکانسهای بالا (تربل). شما میتوانید سطح هر باند را تغییر دهید، اما نمیتوانید فرکانس و عرض آن را تغییر دهید. این نوع اکولایزر به شما اجازه میدهد که با سادگی و سرعت صدای خود را تعادل بخشید. این نوع اکولایزر در بسیاری از دستگاههای پخش صوتی مانند رادیو، استریو، هدفون و غیره استفاده میشود.
-اکولایزر یک ابزار قدرتمند و کاربردی در صنعت صوتی و موسیقی است. با استفاده از اکولایزر میتوانید:
-با استفاده از اکولایزر میتوانید کیفیت صدای خود را بهبود بخشید و فرکانسهای نامطلوب را حذف یا کم کنید. برای مثال، ممکن است صدای خود را خشن، تار، تیره یا خنث
ی شنیده شود. با استفاده از اکولایزر میتوانید این مشکلات را رفع کنید و صدای خود را روشن، شفاف، گرم و زنده کنید. همچنین میتوانید فرکانسهایی را که برای نوع موسیقی یا سبک صدای خود مناسب هستند، برجسته کنید و صدای خود را با توجه به هدف و مخاطب خود شخصیسازی کنید.
-با استفاده از اکولایزر میتوانید باس و تربل صدای خود را تقویت کنید و حجم صدا را افزایش دهید. باس فرکانسهای پایین صدا را نشان میدهد که برای ایجاد حس عمق، قدرت و سنگینی در صدا مهم هستند. تربل فرکانسهای بالای صدا را نشان میدهد که برای ایجاد حس جزئیات، شفافیت و روشنی در صدا مهم هستند. با تقویت باس و تربل میتوانید صدای خود را پربار، جذاب و دلنشین کنید. همچنین با افزایش حجم صدا میتوانید صدای خود را بلندتر و قویتر شنیده شود.
-با استفاده از اکولایزر میتوانید نویز و تداخلات صوتی را حذف یا کم کنید. نویز و تداخلات صوتی ممکن است به دلایل مختلف در سیگنال صوتی وارد شوند، مانند کیفیت پایین منبع صوتی، عدم همخوانی دستگاههای صوتی، نقص در کابلها یا محل قرارگیری بلندگوها. این عوامل ممکن است باعث شوند که صدای خود را با سر و صدا، خش خش، جیر جیر یا سوت زن شنیده شود. با استفاده از اکولایزر م
یتوانید فرکانسهایی را که منشأ نویز و تداخلات هستند، کاهش دهید و صدای خود را تمیز، صاف و بدون اغتشاش شنیده شود.
-با استفاده از اکولایزر میتوانید خلاقیت و تنوع خود را در ساخت موسیقی و میکس به نمایش بگذارید. با استفاده از اکولایزر میتوانید صدای خود را با تغییر فرکانسهای مختلف، تبدیل به صدای دیگری کنید. برای مثال، میتوانید صدای گیتار را به صدای پیانو تبدیل کنید، صدای خواننده را به صدای ربات تبدیل کنید، صدای طبیعت را به صدای فضایی تبدیل کنید و غیره. با استفاده از اکولایزر میتوانید صدای خود را با سبکها و ژانرهای مختلف موسیقی هماهنگ کنید و آثار جدید و منحصر به فرد خلق کنید.
-اگر شما هم دوست دارید که صدای خود را با استفاده از اکولایزر بهینه کنید، ممکن است به دنبال بهترین اکولایزرهای صوتی برای ویندوز 10 در سال 2023 باشید. در این بخش به شما سه نمونه از این اکولایزرها را معرفی خواهیم کرد که همگی دارای ویژگیها و قابلیتهای منحصر به فرد هستند. این سه نمونه عبارتند از:
-Equalizer APO یک اکولایزر پارامتریک حرفهای است که به شما اجازه میدهد که تقریبا هر نوع تغییرات را بر روی صدای خود اعمال کنید. این اکولایزر دارای 20 باند قابل تغ
ییر است و شما میتوانید فرکانس، عرض و سطح هر باند را به دلخواه خود تنظیم کنید. همچنین میتوانید از افکتهای مختلفی مانند ریورب، کمپرسور، لیمیتر، گیت و غیره استفاده کنید. این اکولایزر با تمام برنامهها و دستگاههای صوتی سازگار است و به راحتی قابل نصب و تنظیم است. این اکولایزر را میتوانید از این لینک دانلود کنید.
-Viper4Windows یک اکولایزر گرافیکی پیشرفته است که به شما اجازه میدهد که صدای خود را با استفاده از 18 باند قابل تغییر، تقویت کنید. این اکولایزر دارای حالتهای مختلفی مانند موزیک، فیلم، بازی، صدای زنده و غیره است که شما میتوانید بسته به نوع فعالیت خود از آنها انتخاب کنید. همچنین میتوانید از قابلیتهای دیگری مانند سوراند ساند، باس بوست، کلاریتی، کورکشن و غیره استفاده کنید. این اکولایزر با تمام برنامهها و دستگاههای صوتی سازگار است و به راحتی قابل نصب و تنظیم است. این اکولایزر را میتوانید از این لینک دانلود کنید.
-Equalizer Pro یک اکولایزر گرافیکی حرفهای است که به شما اجازه میدهد که صدای خود را با استفاده از 10 باند قابل تغییر، بهبود بخشید. این اکولایزر دارای حالتهای مختلفی مانند پاپ، راک، جاز، کلاسیک و غیره است که شما میتوانید بسته به نوع موسیقی خود از آنها استفاده کنید. همچنین میتوانید از قابلیتهای د
یگری مانند بالانس، پریآمپ، لودنس و غیره استفاده کنید. این اکولایزر با تمام برنامهها و دستگاههای صوتی سازگار است و به راحتی قابل نصب و تنظیم است. این اکولایزر را میتوانید از این لینک دانلود کنید.
-در این مقاله با اکولایزر و کاربردهای آن آشنا شدید. اکولایزر یک نوع فیلتر صوتی است که به شما امکان میدهد که سطح فرکانسهای مختلف در یک سیگنال صوتی را تغییر دهید. با استفاده از اکولایزر میتوانید کیفیت صدای خود را بهبود بخشید، باس و تربل را تقویت کنید، نویز و تداخلات صوتی را حذف کنید و خلاقیت و تنوع خود را در ساخت موسیقی و میکس به نمایش بگذارید. همچنین به شما سه نمونه از بهترین اکولایزرهای صوتی برای ویندوز 10 در سال 2023 را معرفی کردیم که همگی دارای ویژگیها و قابلیتهای منحصر به فرد هستند. امیدواریم که این مقاله برای شما مفید و جالب بوده باشد. در پایان، به پنج سوال متداول درباره اکولایزر پاسخ خواهیم داد.
-پاسخ: بستگی به نوع اکولایزر و دستگاه صوتی شما دارد. بعضی از اکولایزرها دارای یک دکمه یا کلید روشن/خاموش هستند که با فشار دادن آن م
یتوانید اکولایزر را روشن یا خاموش کنید. بعضی از اکولایزرها نیاز به نصب و اجرای یک نرمافزار دارند که با باز کردن آن میتوانید اکولایزر را فعال یا غیرفعال کنید. بعضی از اکولایزرها هم به صورت خودکار با شناسایی نوع صدا یا موسیقی، روشن یا خاموش میشوند.
-پاسخ: بستگی به نوع اکولایزر و سلیقه شما دارد. بعضی از اکولایزرها دارای حالتهای پیشفرض هستند که شما میتوانید بسته به نوع صدا یا موسیقی، از آنها استفاده کنید. بعضی از اکولایزرها هم به شما اجازه میدهند که با تغییر سطح، فرکانس و عرض باندها، صدای خود را دستی تنظیم کنید. برای تنظیم اکولایزر بهتر است که به چند نکته توجه کنید:
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ه صوتی شما دارد. بعضی از اکولایزرها به صورت خودکار با دستگاههای صوتی دیگر همخوان میشوند و شما نیازی به تنظیم آنها ندارید. بعضی از اکولایزرها نیاز به تنظیم دستی دارند و شما باید با استفاده از کابلها، پورتها، بلوتوث یا وایفای، آنها را به دستگاههای صوتی دیگر متصل کنید. برای همخوان کردن اکولایزر با دستگاههای صوتی دیگر بهتر است که به چند نکته توجه کنید:
-پاسخ: بستگی به نوع و مدل گوشی هوشمند شما دارد. بعضی از گوشیهای هوشمند دارای یک اکولایزر ساده در تنظیمات صدای خود هستند که شما میتوانید با استفاده از آن، صدای خود را تغییر دهید. بعضی از گوشی های هوشمند نیاز به نصب و اجرای یک نرمافزار اکولایزر دارند که شما میتوانید با استفاده از آن، صدای خود را با دقت بیشتری تغییر دهید. بعضی از گوشیهای هوشمند هم با اکولایزرهای خارجی مانند اکولایزرهای بلوتوث یا وایفای قابل اتصال هستند. برای همخوان کردن اکولایزر با گوشی هوشمند خود بهتر است که به چند نکته توجه کنید:
-پاسخ: بستگی به سطح و نحوه استفاده شما از اکولایزر دارد. استفاده بیرویه و غیرصحیح از اکولایزر ممکن است باعث آسیب به شنوایی شما شود. برای سازگار کردن اکولایزر با سلامت شنوایی خود بهتر است که به چند نکته توجه کنید:
-نوایی شما شود.
امیدواریم که این مقاله برای شما مفید و جالب بوده باشد. اگر سوال یا نظر دیگری درباره اکولایزر دارید، ما را در قسمت نظرات با خبر کنید. با تشکر از همراهی شما.
401be4b1e0If you are a fan of South African music, especially the Amapiano genre, you have probably heard of Askies I'm Sorry by De Mthuda. This song is one of the latest releases from the talented record producer and DJ, featuring Just Bheki, Mkeyz, and Da Muziqal Chef. It is a catchy and upbeat tune that will make you want to dance and groove along. But who is De Mthuda, and what is Amapiano? And what does Fakaza have to do with it? In this article, we will answer these questions and more.
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De Mthuda's real name is Mthuthuzeli Gift Khoza. He was born and raised in Vosloorus, a township east of Johannesburg. He started producing music in 2010 when he was still in high school, but he dropped out in grade 11 to pursue his music career. He was inspired by artists like Black Coffee, Oskido, DJ Tira, and DJ Fresh. He is best known for his singles Shesha Geza and John Wick, which were certified gold by RiSA and nominated for Record of the Year at the South African Music Awards. He has also collaborated with other Amapiano stars like Kabza De Small, Njelic, Daliwonga, Focalistic, and Sir Trill.
-De Mthuda has released several songs and albums that have made him one of the most prominent figures in the Amapiano scene. Some of his popular songs include:
-Some of his popular albums include:
-Amapiano is a subgenre of house music that emerged in South Africa in the mid-2010s. It is a hybrid of deep house, jazz, lounge music, Kwaito, Tribal house, and R&B. It is characterized by synths, wide percussive basslines, low tempo rhythms, high-pitched piano melodies, log drums, vocals, and samples. The word Amapiano means "the pianos" in Zulu or Xhosa.
-The origin and history of Amapiano are disputed, as there are various accounts of how it started and who created it. Some say it originated in Pretoria, where Bacardi, another house music subgenre, was popular. Others say it originated in Johannesburg, where different townships like Soweto, Alexandra, Vosloorus, and Katlehong contributed to its development. Some of the pioneers and influencers of Amapiano include DJ Stokie, Kabza De Small, JazziDisciples, Vigro Deep
Amapiano is a versatile and diverse genre that can incorporate various elements and influences from other genres and cultures. Some of the characteristics and influences of Amapiano include:
-Amapiano has become one of the most popular and influential genres in South Africa and beyond. It has gained a huge fan base and following across different age groups, social classes, and regions. It has also spawned various subgenres and styles, such as Yanos (a more commercial and mainstream version of Amapiano), Scorpion Kings (a style popularized by Kabza De Small and DJ Maphorisa), Private School Piano (a more sophisticated and refined version of Amapiano), and Barcadi Piano (a fusion of Amapiano and Bacardi).
-Amapiano has also crossed borders and reached international audiences. It has been featured on global platforms and media outlets, such as Spotify, Apple Music, BBC Radio 1Xtra, Boiler Room, Mixmag, The Guardian, and The New York Times. It has also inspired and collaborated with artists from other countries and continents, such as Nigeria (Burna Boy, Wizkid), Ghana (Stonebwoy), Kenya (Sauti Sol), Tanzania (Diamond Platnumz), France (David Guetta), UK (Jorja Smith), USA (Drake), and Brazil (Anitta).
-Fakaza is a Zulu word that means "to share" or "to distribute". It is also the name of a popular South African music site that allows users to download and stream various genres of music for free. The site was founded in 2016 by a group of music enthusiasts who wanted to provide a platform for local artists to showcase their talent and reach a wider audience.
-Fakaza is one of the best sources for finding and downloading South African music online. Some of the features and benefits of the Fakaza music site include:
- -If you want to download Askies I'm Sorry by De Mthuda from Fakaza, you can follow these simple steps:
-In conclusion, Askies I'm Sorry by De Mthuda is a hit Amapiano song that you should not miss. It showcases the talent and creativity of De Mthuda, one of the leading record producers and DJs in South Africa. It also represents the Amapiano genre, which is a unique and vibrant style of house music that has taken over the country and the world. And if you want to download this song for free, you can use Fakaza, which is a reliable and convenient music site that offers a variety of genres and songs. So what are you waiting for? Go ahead and download Askies I'm Sorry by De Mthuda from Fakaza today!
-Askies is a slang word that means "sorry" or "excuse me" in South African English. It is derived from the Afrikaans word "asseblief", which means "please".
-Askies I'm Sorry by De Mthuda features three vocalists: Just Bheki, Mkeyz, and Da Muziqal Chef. They are all South African singers who have worked with De Mthuda before on other songs.
-You can listen to Askies I'm Sorry by De Mthuda on various streaming platforms, such as YouTube, Spotify, Apple Music, Deezer, SoundCloud, Audiomack, and more. You can also download it from Fakaza or other music sites.
-Some other Amapiano songs that you should check out include:
-You can learn more about De Mthuda and Amapiano by following them on social media platforms, such as Facebook, Twitter, Instagram, TikTok, and more. You can also visit their official websites or blogs, where they post updates and news about their music. You can also watch interviews or documentaries about them on YouTube or other video sites.
197e85843dIf you are a fan of Brawl Stars, you probably know how important gems and coins are in this game. Gems and coins are the currencies that you need to unlock new brawlers, skins, power points, star powers, gadgets, and more. But how can you get enough gems and coins without spending a fortune? Is there a way to get unlimited gems and coins for free? In this article, we will tell you everything you need to know about Brawl Stars hack APK download 2022, the modded version of the game that claims to give you unlimited resources. But before we get into that, let's first take a look at what Brawl Stars is and why it is so popular.
-Brawl Stars is a mobile twin-stick shooter game developed by Supercell, the makers of Clash of Clans and Clash Royale. In this game, you can choose from over 20 different brawlers, each with their own unique abilities and weapons, and compete in various game modes with other players from around the world. You can team up with your friends or play solo, depending on your preference.
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Brawl Stars is a game that is easy to pick up and play, but hard to master. The matches are short and intense, lasting for only three minutes or less. You have to use your skills, strategy, and teamwork to defeat your enemies and win the game. You can also customize your brawlers with different skins and pins to show off your personality.
-Brawl Stars has many features that make it an exciting and diverse game. Here are some of them:
-Brawl Stars has several game modes that you can choose from, each with a different objective and rules. Some of the game modes are:
-Brawl Stars has a diverse roster of brawlers that you can unlock and play with. Each brawler has a different class, such as fighter, sharpshooter, heavyweight, thrower, support, assassin, or chromatic. Each brawler also has a different rarity, such as common, rare, super rare, epic, mythic, legendary, or chromatic. The higher the rarity, the harder it is to get the brawler. You can also unlock different skins for your brawlers, some of which are exclusive to certain events or seasons.
-Brawl Stars has a seasonal system called the brawl pass, which allows you to earn rewards by playing the game and completing quests. The brawl pass has two tracks: the free track and the premium track. The free track gives you basic rewards, such as coins, power points, and brawl boxes. The premium track gives you more rewards, such as gems, skins, pins, and exclusive brawlers. You can access the premium track by buying the brawl pass with gems.
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Gems and coins are the two main currencies in Brawl Stars that you need to progress in the game and unlock more content. Here is why they are important:
-Gems are the rarest and most valuable currency in Brawl Stars. You can use gems to buy various items in the shop, such as:
-Coins are the most common and basic currency in Brawl Stars. You can use coins to upgrade your brawlers and unlock their star powers and gadgets. Upgrading your brawlers increases their health, damage, and super charge rate. Unlocking their star powers and gadgets gives them extra abilities that can change the outcome of a match. You can also use coins to buy power points in the shop.
-There are two ways to get gems and coins in Brawl Stars: the legit way and the hack way. Let's see what they are:
-The legit way to get gems and coins in Brawl Stars is to play the game and earn them through various means. Some of the legit ways are:
-The simplest way to get gems and coins is to play the game and win matches. You will earn tokens for every match you play, which you can use to open brawl boxes. Brawl boxes contain random rewards, such as gems, coins, power points, or brawlers. You can also complete quests that give you tokens or other rewards. Quests are tasks that require you to do something specific in the game, such as winning a certain number of matches with a specific brawler or mode.
-Another way to get gems and coins is to open brawl boxes and hope for the best. Brawl boxes have a chance to contain gems or coins, along with other items. The chance of getting gems or coins depends on the type of brawl box you open. There are three types of brawl boxes: normal brawl boxes, big boxes, and mega boxes. Normal brawl boxes cost 100 tokens to open and have a 9% chance of containing gems or coins. Big boxes cost 300 tokens or 30 gems to open and have a 27% chance of containing gems or coins. Mega boxes cost 1500 tokens or 80 gems to open and have a 135% chance of containing gems or coins.
-The last way to get gems and coins is to spend real money in the shop. You can buy gems with real money and use them to buy coins or other items in the shop. You can also buy offers that give you bundles of gems, coins, power points, or brawlers at a discounted price. However, this method is not free and may not be affordable for everyone.
-The hack way to get gems and coins in Brawl Stars is to download a modded APK file that gives you unlimited resources. A modded APK file is a modified version of the original game file that has been altered to give you some advantages or features that are not available in the official game. For example, a Brawl Stars hack APK may give you unlimited gems and coins, unlock all brawlers and skins, or enable cheats such as auto-aim or god mode.
-To use a Brawl Stars hack APK, you need to download it from a third-party website that offers such files. You can search for "Brawl Stars hack APK download 2022" on Google or any other search engine and find many websites that claim to provide such files. However, you need to be careful and cautious when downloading such files, as they may not be safe or reliable. Here are some of the risks of using a hack APK for Brawl Stars:
-Using a hack APK for Brawl Stars may seem tempting and appealing, but it is not worth it in the long run. Here are some of the reasons why you should avoid using a hack APK for Brawl Stars:
-One of the main problems with using a hack APK for Brawl Stars is that it may not work or be outdated. Hack APKs are not official or authorized by Supercell, the developer of Brawl Stars. Therefore, they are not compatible with the latest version of the game or the server. This means that you may not be able to play the game properly or access all the features and content. You may also encounter errors, glitches, bugs, or crashes that ruin your gaming experience.
-Another problem with using a hack APK for Brawl Stars is that it may contain malware or viruses that can harm your device or steal your personal information. Hack APKs are not verified or tested by any trusted source, so you cannot be sure what they contain or what they do. They may have hidden codes or programs that can infect your device with malware or viruses that can damage your system, delete your files, spy on your activities, or steal your data. You may also expose yourself to hackers or scammers who can access your account or device and use them for malicious purposes.
-The last problem with using a hack APK for Brawl Stars is that it may get your account banned or suspended by Supercell. Supercell has a strict policy against cheating or hacking in their games, and they have a system that can detect and punish such behavior. If you use a hack APK for Brawl Stars, you are violating the terms of service and the fair play policy of the game. This means that you are risking losing your account and all your progress and achievements. You may also lose access to other Supercell games or services.
-Brawl Stars is a fun and addictive game that requires gems and coins to progress and unlock more content. There are legit ways and hack ways to get gems and coins, but the hack ways are risky and not recommended. The best way to enjoy Brawl Stars is to play fair and have fun with your friends and other players from around the world.
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-A: There may be some websites that claim to offer working Brawl Stars hack APKs in 2022, but they are not reliable or trustworthy. Most of them are either fake, outdated, infected, or detected by Supercell. Therefore, we do not recommend using any Brawl Stars hack APK in 2022.
-A: The best way to get free gems and coins in Brawl Stars without hacking is to play the game and earn them through legit ways. You can play the game and complete quests, open brawl boxes and get lucky, or spend real money in the shop if you can afford it.
-A A: Some of the tips and tricks to play better in Brawl Stars are: - Choose the right brawler for the right mode and map. Different brawlers have different strengths and weaknesses, and some are more suited for certain modes and maps than others. For example, long-range brawlers are good for open maps, while short-range brawlers are good for close-quarters maps. - Learn the abilities and mechanics of each brawler. Each brawler has a unique basic attack, super, star power, and gadget that can affect their performance and strategy. You should know how to use them effectively and efficiently, as well as how to counter them when facing them. - Communicate and cooperate with your teammates. Brawl Stars is a team-based game that requires coordination and teamwork to win. You should use the chat or the ping system to communicate with your teammates, such as calling for help, signaling your intentions, or warning about enemies. You should also support your teammates by healing them, protecting them, or assisting them in attacking or defending. - Practice and improve your skills. Brawl Stars is a game that requires skill and reflexes to play well. You should practice and improve your skills by playing different modes and maps, trying different brawlers and strategies, and learning from your mistakes and feedback. You can also watch replays or videos of other players to see how they play and what they do.
A: Brawl Stars is available for both Android and iOS devices. You can download it from the Google Play Store or the App Store, depending on your device. You need to have a compatible device that meets the minimum requirements of the game, such as Android 4.3 or higher or iOS 9.0 or higher.
-A: If you have any issues or questions about Brawl Stars, you can contact Supercell through their official channels, such as their website, their social media accounts, or their in-game support. You can also visit their help center or their community forums to find answers or solutions to common problems or queries.
197e85843dIf you are looking for a fun and addictive puzzle game to play on your Android device, you should try Candy Crush Saga. This game has been downloaded by over a billion people and has become one of the most popular games in the world. But what if you want to enjoy the game without any limitations or restrictions? In that case, you should download Candy Crush Saga Mod APK, which is a modified version of the game that gives you unlimited access to all the features and levels. In this article, we will tell you what Candy Crush Saga is, why you should download the modded version, and how to do it.
-Candy Crush Saga is a puzzle game that was released in 2012 by King, a Swedish game developer. The game is based on matching three or more candies of the same color to clear them from the board and complete various objectives. The game has hundreds of levels, each with different challenges and goals. The game also has different modes, such as timed levels, jelly levels, ingredient levels, and more. The game is free to play, but you can also buy extra moves, boosters, lives, and other items with real money.
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Some of the features that make Candy Crush Saga so popular are:
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Is Candy Crush Saga Mod APK safe to use? | -Yes, Candy Crush Saga Mod APK is safe to use as long as you download it from a trusted source. However, you should be aware that using a modded version of the game may violate the terms and conditions of the original game and may result in your account being banned or suspended. | -
Does Candy Crush Saga Mod APK work offline? | -Yes, Candy Crush Saga Mod APK works offline as well as online. You can play the game without an internet connection and still enjoy all the features and levels. However, you may not be able to access some of the social features, such as leaderboards and events, when you are offline. | -
Can I update Candy Crush Saga Mod APK? | -Yes, you can update Candy Crush Saga Mod APK whenever there is a new version available. However, you may need to uninstall the previous version and install the new one manually. You may also lose your progress and data if you update the modded version of the game. | -
Can I sync Candy Crush Saga Mod APK with Facebook? | -No, you cannot sync Candy Crush Saga Mod APK with Facebook or any other social media platform. This is because the modded version of the game is not compatible with the official version and may cause errors or conflicts. If you want to sync your progress and data with Facebook, you should use the original version of the game. | -
Can I play Candy Crush Saga Mod APK on other devices? | -Yes, you can play Candy Crush Saga Mod APK on other devices as long as they are Android devices. You can transfer the modded APK file from one device to another using a USB cable or a file-sharing app. However, you may need to enable unknown sources on each device before installing the modded version of the game. | -
Do you love racing games? Do you love the Disney Pixar Cars movies? If you answered yes to both questions, then you will love Cars Daredevil Garage APK. This is a racing game that lets you join Lightning McQueen, Mater, and all of your favorite Cars characters as you power through heart-racing stunts with over 180 vehicles. You can crank up the speed on over 15 tracks that take crazy twists and turns through the beach, the backyard, and the bowling alley. You can also scan your actual Mattel die-cast cars to unlock more fun in the game. In this article, we will tell you everything you need to know about Cars Daredevil Garage APK, including its features, how to download and install it on your Android device, and some tips and tricks for playing it.
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Cars Daredevil Garage APK is a game that is packed with features that will keep you entertained for hours. Here are some of the features that you can enjoy in this game:
-You can choose from over 180 vehicles to stunt with in this game, including cars from different categories such as World Grand Prix, Piston Cup, Radiator Springs, Ye Left Turn Inn, Tuners, Lost and Found, Airport Adventure, Race Fans, Pit Crew, Dinoco, Tokyo Party Palace Chaos, Ice Racers, Neon Racers, Silver Racers, and more. You can also customize your cars with different colors, stickers, wheels, and accessories.
-You can power through 15 tracks that take you to different locations such as the beach, the backyard, and the bowling alley. Each track has its own challenges and obstacles that will test your skills and reflexes. You can perform amazing stunts such as jumps, loops, skids, drifts, flips, and more. You can also collect coins and stars along the way to earn extra points and rewards.
-If you have any Mattel die-cast cars from the Cars movie franchise, you can scan them using your device's camera to unlock them in the game. You can then use them to stunt with in the app. The more cars you scan, the more fun you will have in the game.
-If you want to access more tracks and worlds in the game, you can purchase them using real money or coins that you earn in the game. With each new world purchase, you will also get a free hero car that is exclusive to that world. For example, if you buy the beach world, you will get a free beach buggy car.
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Before you can install any APK file on your device, you need to enable the option to allow installation from unknown sources. This is a security measure that prevents malicious apps from harming your device. To do this, go to your device settings and look for the security or privacy option. Then, find the unknown sources option and toggle it on. You may see a warning message that tells you the risks of installing apps from unknown sources. Just tap OK to proceed.
-Next, you need to download the APK file of Cars Daredevil Garage from a trusted source. You can use any web browser to search for the file online. Make sure that the source is reliable and has positive reviews from other users. You can also use the link below to download the file directly from our website. The file size is about 100 MB, so make sure you have enough space on your device and a stable internet connection.
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-Once you have downloaded the file, you need to locate it on your device and install it. You can use any file manager app to find the file in your downloads folder or any other location where you saved it. Then, tap on the file and select install. You may see a pop-up message that asks for your permission to install the app. Just tap install again and wait for the installation process to finish.
-After the installation is complete, you can launch the game by tapping on its icon on your home screen or app drawer. You may see a splash screen that shows the game's logo and some loading animations. Then, you will see the main menu of the game where you can choose to play, scan cars, customize cars, or access other options. You can also sign in with your Google Play Games account to save your progress and achievements. Now, you are ready to enjoy Cars Daredevil Garage APK on your Android device.
-Cars Daredevil Garage APK is a fun and exciting racing game for kids, but it can also be challenging at times. Here are some tips and tricks that can help you improve your gameplay and have more fun:
-In each track, you will see some boosters and power-ups that can help you speed up, perform stunts, or avoid obstacles. For example, you can use rockets, magnets, shields, or turbo boosts to gain an edge over your opponents or obstacles. However, these boosters and power-ups are limited and have cooldowns, so you need to use them wisely and strategically. Don't waste them on easy parts of the track or when you are already ahead of everyone else. Save them for when you really need them or when they can make a big difference in your performance.
-As you play through the tracks, you will see some coins and stars that you can collect by driving over them or performing stunts. These coins and stars are very important because they allow you to upgrade your cars and unlock new ones. Upgrading your cars can improve their speed, acceleration, handling, and stunt abilities. Unlocking new cars can give you access to different features and styles that suit your preferences. Therefore, try to collect as many coins and stars as possible in each track and spend them wisely on upgrading or unlocking your cars.
-Cars Daredevil Garage APK has over 180 vehicles and 15 tracks that you can choose from, so there is a lot of variety and diversity in the game. Each car has its own strengths and weaknesses, and each track has its own challenges and opportunities. Therefore, it is a good idea to try different cars and tracks to find your favorite combination that matches your play style and personality. You may discover some hidden gems or surprises that make the game more fun and enjoyable for you.
-If you want to earn more coins, stars, or other rewards in the game, you can watch some videos or complete some offers that are available in the game's menu. These videos or offers are usually short and simple, such as watching an ad, downloading another app, or answering
a survey, etc. By doing these, you can earn more coins, stars, or even free cars that you can use in the game. However, be careful and selective about the videos or offers that you watch or complete, as some of them may be spammy or harmful to your device. Only choose the ones that are from trusted sources and that do not ask for your personal information or access to your device.
-Cars Daredevil Garage APK is a fun and exciting racing game for kids that lets you play with your favorite Cars characters and vehicles. You can choose from over 180 vehicles and 15 tracks that offer crazy stunts and challenges. You can also scan your Mattel die-cast cars to unlock more fun in the game. You can download and install the game on your Android device easily and enjoy it anytime and anywhere. You can also use some tips and tricks to improve your gameplay and have more fun. Cars Daredevil Garage APK is a game that will keep you entertained for hours and make you feel like a daredevil racer.
-Here are some frequently asked questions about Cars Daredevil Garage APK:
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-A: Yes, Cars Daredevil Garage APK is free to play, but it also offers some in-app purchases that can enhance your gaming experience. You can buy more coins, stars, tracks, or cars using real money or coins that you earn in the game. However, these purchases are optional and not required to enjoy the game.
-A: To scan your Mattel die-cast cars to unlock them in the game, you need to have a device with a camera and an internet connection. Then, you need to go to the scan menu in the game and follow the instructions on how to scan your car. You need to place your car on a flat surface with good lighting and hold your device over it until it recognizes the car. Then, you will see a confirmation message that tells you that you have unlocked the car in the game.
-A: To customize your cars in the game, you need to go to the customize menu in the game and select the car that you want to modify. Then, you will see different options for changing the color, stickers, wheels, and accessories of your car. You can also use coins or stars to buy more options for customizing your car.
-A: To save your progress and achievements in the game, you need to sign in with your Google Play Games account. This will allow you to sync your data across different devices and access leaderboards and achievements. You can also share your progress and achievements with your friends on social media.
197e85843dIf you are looking for some fun and effective ways to help your child learn new skills and knowledge, you might want to consider educational games. Educational games are games that are designed to teach children various concepts and topics in a playful and interactive way. They can also provide a stimulating and engaging learning environment that motivates children to stay focused and interested in their learning goals.
| |There are many educational games available online that you can download for free and use with your child. These games cover different subject areas such as math, language arts, science, art, and more. They also cater to different age groups and skill levels, so you can find something suitable for your child's needs and preferences.
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In this article, we will explore how to choose educational games for kids-6 years old, what benefits they can offer, and how to use them effectively. We will also provide some examples of free download educational games that you can try with your child.
| |When choosing educational games for your child, there are some factors that you should consider. Here are some tips and criteria to help you make a smart choice:
| |Here are some examples of free download educational games for kids-6 years old that meet the criteria:
-Game | -Topic | -Description | -
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ABCmouse.com Early Learning Academy | -Math, Language Arts, Science, Art, and more | -A comprehensive and interactive learning program that covers various subjects and skills for preschool to 2nd grade. It has over 10,000 activities, games, books, songs, and videos that are aligned with the Common Core Standards. | -
PBS KIDS Games | -Math, Science, Social Studies, Creativity, and more | -A collection of over 200 games featuring popular PBS KIDS characters such as Curious George, Daniel Tiger, and Wild Kratts. The games are designed to help kids learn and explore different topics and themes in a fun and engaging way. | -
CodeSpark Academy: Kids Coding | -Coding, Logic, Problem-Solving, Creativity, and more | -A game-based learning platform that teaches kids the basics of coding and computational thinking. It uses a kid-friendly visual programming language that does not require reading or typing. It also has puzzles, challenges, projects, and mini-games that foster creativity and collaboration. | -
BrainPOP Jr. Movie of the Week | -Science, Social Studies, Reading, Writing, Math, Health, Arts, and Technology | -A weekly animated movie that introduces kids to various topics and concepts in an entertaining and informative way. It also has quizzes, activities, and games that reinforce the learning objectives and skills. | -
Duolingo ABC - Learn to Read | -Reading, Writing, Phonics, Vocabulary, and more | -A game-based app that helps kids learn to read in English. It has over 300 fun and interactive lessons that teach the alphabet, phonics, sight words, spelling, and more. It also adapts to each child's level and progress. | -
Educational games can offer many benefits for kids-6 years old. They can help kids:
-There is evidence and research that supports the benefits of educational games for kids-6 years old. For example, a study by the Joan Ganz Cooney Center found that educational games can improve kids' math skills, especially when they are played with a parent or a teacher. Another study by the University of California, Irvine found that educational games can improve kids' reading skills, especially when they are combined with traditional instruction. A third study by the University of Wisconsin-Madison found that educational games can improve kids' science skills, especially when they are designed to promote inquiry and exploration.
-Educational games can be used in different ways to enhance your child's learning experience. Here are some suggestions and guidelines for using games effectively and safely:
-Here are some examples of how to use educational games for kids-6 years old in different ways:
-Game | -How to Use | -
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ABCmouse.com Early Learning Academy | -You can use this game as a comprehensive learning program for your child. You can create a personalized learning path for your child based on their age and interests. You can also track your child's progress and achievements through the dashboard. You can also play the games with your child and help them with the activities. | -
PBS KIDS Games | -You can use this game as a supplement to your child's curriculum and interests. You can choose games that match your child's grade level and subject area. You can also explore games that feature your child's favorite PBS KIDS characters. You can also watch the related TV shows or videos with your child and discuss the topics. | -
CodeSpark Academy: Kids Coding | -You can use this game as an introduction to coding and computational thinking for your child. You can help your child learn the basics of coding and logic through the visual programming language. You can also encourage your child to create their own games and projects using the game's tools and resources. | -
BrainPOP Jr. Movie of the Week | -You can use this game as a way to spark your child's curiosity and interest in various topics and concepts. You can watch the movie of the week with your child and learn something new together. You can also play the related quizzes, activities, and games with your child and test their knowledge and skills. | -
Duolingo ABC - Learn to Read | -You can use this game as a support for your child's reading development. You can help your child learn the alphabet, phonics, sight words, spelling, and more through the game's lessons. You can also read books or stories with your child and practice their reading skills. | -
Educational games are a great way to help your child learn new skills and knowledge in a fun and engaging way. They can also provide many benefits for your child's cognitive, academic, social, and emotional development. However, not all games are created equal, so you should be careful and selective when choosing educational games for your child. You should also use them wisely and effectively, and make sure they are appropriate and safe for your child.
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If you are looking for some free download educational games for kids-6 years old, you can try some of the examples we provided in this article. They are all well-designed, user-friendly, and educational games that cover different subject areas and skills. They are also fun and interesting for kids-6 years old, and they can be used in different ways to enhance their learning experience.
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-Si usted está buscando un divertido y adictivo juego de conducción basado en la física, es posible que desee echa un vistazo a Hill Climb Racing. Este juego está disponible para dispositivos móviles y PC, y te mantendrá entretenido durante horas. En este artículo, te mostraremos cómo descargar Hill Climb Racing en tu PC, y compartiremos algunos consejos y trucos para ayudarte a dominar el juego.
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Aunque Hill Climb Racing está diseñado principalmente para dispositivos móviles, también puedes disfrutarlo en tu PC. Jugar Hill Climb Racing en PC tiene algunas ventajas, como:
-Puede encontrar el icono de Microsoft Store en su barra de tareas o menú de inicio. Haga clic en él para abrir la tienda.
-En el cuadro de búsqueda en la esquina superior derecha de la tienda, escriba "Hill Climb Racing" y pulse enter. Verá una lista de resultados que coinciden con su consulta.
-Encuentra el juego Hill Climb Racing de la lista de resultados, y haga clic en él para abrir su página de detalles. Verá un botón Get en el lado derecho de la página. Haga clic en él para comenzar a descargar el juego. Es posible que necesite iniciar sesión con su cuenta de Microsoft si aún no lo ha hecho.
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-Otra forma de descargar Hill Climb Racing en tu PC es utilizar un emulador de Android. Un emulador de Android es un software que simula un dispositivo Android en su PC, lo que le permite ejecutar aplicaciones y juegos de Android en su PC. Hay muchos emuladores de Android disponibles en línea, como BlueStacks, NoxPlayer, LDPlayer y más. Estos son los pasos a seguir:
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-En Google Play Store, escribe "Hill Climb Racing" en el cuadro de búsqueda y pulsa enter. Verás una lista de resultados que coinciden con tu consulta.
- -Encuentra el juego Hill Climb Racing de la lista de resultados, y haga clic en él para abrir su página de detalles. Verá un botón de instalación en el lado derecho de la página. Haga clic en él para comenzar a descargar e instalar el juego. Una vez completada la instalación, puedes iniciar el juego desde Google Play Store o desde tu pantalla de inicio o desde el cajón de aplicaciones. Verás una pantalla de bienvenida con el logotipo de Fingersoft, seguido del menú principal del juego. Ahora puedes empezar a jugar Hill Climb Racing en tu PC.
-Hill Climb Racing es un juego divertido y adictivo, pero también puede ser desafiante y frustrante a veces. Para ayudarte a mejorar tus habilidades y disfrutar más del juego, aquí hay algunos consejos y trucos que puedes usar:
-Hill Climb Racing tiene más de 30 vehículos que puedes elegir, cada uno con diferentes características y habilidades. Algunos vehículos son más rápidos, algunos son más estables, algunos son más ágiles y algunos tienen características especiales, como amplificadores o armas. Dependiendo de la etapa que estés jugando, es posible que desees elegir un vehículo diferente que se adapte al terreno y al nivel de dificultad. Por ejemplo, si usted está jugando un escenario con colinas empinadas y superficies ásperas, es posible que desee utilizar un vehículo que tiene una buena suspensión y tracción, como un jeep o un camión monstruo. Si está jugando una etapa con carreteras lisas y largas distancias, es posible que desee usar un vehículo que tenga alta velocidad y eficiencia de combustible, como una bicicleta o un automóvil deportivo.
-A medida que conduce su vehículo a través de las etapas, se encontrará con varias monedas y bonos que usted puede recoger. Las monedas son la moneda principal del juego, y se puede utilizar para comprar nuevos vehículos y actualizar los existentes. Los bonos son artículos especiales que pueden darle beneficios adicionales, como combustible, velocidad, tiempo de aire o protección. Algunos de los bonos que puedes encontrar son:
-Trata de recoger tantas monedas y bonos como puedas, ya que pueden ayudarle a mejorar su puntuación y el progreso en el juego.
-Hill Climb Racing no se trata solo de conducir del punto A al punto B. También se trata de divertirse y mostrar sus habilidades. Puede realizar varias acrobacias y trucos con su vehículo, tales como volteretas, caballitos, saltos y rollos. Realizar acrobacias y trucos puede ganar más puntos, lo que puede aumentar su puntuación y rango. Sin embargo, realizar acrobacias y trucos también implica algunos riesgos, como perder el equilibrio, estrellarse o quedarse sin combustible. Por lo tanto, tienes que ser cuidadoso e inteligente sobre cuándo y cómo realizarlos. Aquí hay algunos consejos para ayudarte a realizar acrobacias y trucos:
-Hill Climb Racing no es un juego fácil. Está lleno de desafíos y peligros que pueden impedirte llegar a tu destino. Usted tiene que tener cuidado con varios obstáculos y niveles de combustible que pueden afectar su rendimiento y supervivencia. Algunos de los obstáculos que puedes encontrar son:
-Hill Climb Racing es un divertido y adictivo juego de conducción basado en la física que se puede jugar en dispositivos móviles y PC. Puede elegir entre diferentes vehículos y conducirlos a través de varias etapas con diferentes terrenos y dificultades. También puede actualizar sus vehículos, recoger monedas y bonos, realizar acrobacias y trucos, y cuidado con los obstáculos y los niveles de combustible. Jugar Hill Climb Racing en PC tiene algunas ventajas sobre jugarlo en dispositivos móviles , como jugar en una pantalla más grande, usar un teclado o un ratón, salvar la vida de la batería y el uso de datos, y acceder a más características y opciones. Puedes descargar Hill Climb Racing en tu PC usando Microsoft Store o un emulador de Android. También puede utilizar algunos consejos y trucos para mejorar sus habilidades y disfrutar del juego más. Hill Climb Racing es un juego que te desafiará y te entretendrá al mismo tiempo. Si estás buscando un juego que combine física, conducción y diversión, deberías probar Hill Climb Racing.
-Aquí hay algunas preguntas frecuentes sobre Hill Climb Racing:
-Hay más de 30 etapas en Hill Climb Racing, cada una con diferentes temas, terrenos y dificultades. Algunas de las etapas son Campo, Desierto, Ártico, Luna, Marte, Bosque, Volcán, Montaña Rusa y Planta Nuclear.
-Puedes desbloquear nuevos vehículos en Hill Climb Racing ganando suficientes monedas para comprarlos. Usted puede ganar monedas jugando el juego, recogiéndolos en el camino, realizar acrobacias y trucos, o el uso de bonos. También puede ver anuncios o hacer compras en la aplicación para obtener más monedas.
-Hill Climb Racing no es multijugador, pero tiene una función llamada tablas de clasificación que le permite comparar sus puntuaciones y rangos con otros jugadores de todo el mundo. También puedes retar a tus amigos y familiares compartiendo tus capturas de pantalla o videos de tu juego.
-Hill Climb Racing es gratis para descargar y jugar, pero contiene anuncios y ofrece compras en la aplicación. Puede eliminar los anuncios y obtener más monedas y bonos haciendo compras en la aplicación. También puede desactivar las compras en la aplicación cambiando la configuración del dispositivo.
-Si eres fanático del fútbol (o del fútbol, como algunos lo llaman), probablemente hayas oído hablar de FIFA, la serie de videojuegos de fútbol más popular y realista de EA SPORTS. La última entrega, FIFA 21, ya está disponible y puedes jugar en tu PC con gráficos impresionantes, un juego inmersivo y características emocionantes. En este artículo, te mostraremos cómo descargar FIFA 21 en tu PC desde dos fuentes diferentes: el sitio web de EA y Steam. Pero primero, veamos de qué se trata FIFA 21 y por qué deberías jugarlo.
-FIFA 21 es la 28a edición de la serie de videojuegos de la FIFA, que simula las ligas y torneos de fútbol profesional de todo el mundo. Puede crear su propio equipo personalizado, jugar como sus jugadores favoritos, competir con otros jugadores en línea, o disfrutar de varios modos de juego que ofrecen diferentes desafíos y recompensas. FIFA 21 es alimentado por Frostbite, un motor de juego que ofrece física realista, animaciones, iluminación y efectos de sonido. FIFA 21 también introduce algunas nuevas características y mejoras que lo convierten en el mejor juego de la FIFA. Aquí están algunas de ellas:
-Download ⚹⚹⚹ https://bltlly.com/2v6Lxn
Si quieres descargar FIFA 21 desde el sitio web oficial de EA, debes seguir estos pasos:
-Para acceder al sitio web de EA, necesitas tener una cuenta de EA. Si no tienes uno, puedes crear uno gratis haciendo clic en el botón "Registrarse" en la esquina superior derecha del sitio web. Deberá proporcionar su dirección de correo electrónico, contraseña, fecha de nacimiento, país e idioma preferido. También deberá aceptar los Términos de servicio y la Política de privacidad de EA. Si ya tienes una cuenta de EA, puedes iniciar sesión haciendo clic en el botón "Iniciar sesión" en la esquina superior derecha del sitio web. Tendrá que introducir su dirección de correo electrónico y contraseña.
-Una vez que haya iniciado sesión, puede ir a la página de FIFA 21 haciendo clic en la pestaña "Juegos" en el menú superior y seleccionando "FIFA" de la lista desplegable. Verás tres ediciones de FIFA 21 disponibles para su compra: Standard Edition, Champions Edition y Ultimate Edition. Cada edición viene con diferentes características y bonificaciones, como paquetes adicionales de FUT, iconos de FUT, elementos de modo carrera y más. Puede comparar las ediciones haciendo clic en el botón "Comparar ediciones" debajo del precio. También puede ver los beneficios de pre-orden haciendo clic en el botón "Reservar ahora" debajo de cada edición. Una vez que haya decidido qué edición desea, puede elegir su plataforma haciendo clic en el icono "PC" debajo del nombre de la edición.
-Para descargar y jugar FIFA 21 en tu PC, necesitas tener la aplicación EA Desktop instalada en tu sistema. La aplicación EA Desktop es una nueva plataforma que te permite acceder y gestionar tus juegos de EA, suscripciones y mucho más. Si aún no lo tienes, puedes descargarlo gratis haciendo clic en el botón "Descargar ahora" en la página de la aplicación EA Desktop. Tendrá que ejecutar el archivo de instalación y seguir las instrucciones para completar la instalación. Si ya lo tiene, puede omitir este paso.
-Después de instalar
Después de instalar la aplicación de EA Desktop, debe iniciarla e iniciar sesión en su cuenta de EA. Puede hacer esto haciendo clic en el botón "Iniciar sesión" en la esquina superior derecha de la ventana de la aplicación. Deberá ingresar su dirección de correo electrónico y contraseña. Si ha habilitado la autenticación de dos factores, también tendrá que introducir el código de verificación que recibe en su teléfono o correo electrónico.
-Una vez que haya iniciado sesión, puede encontrar FIFA 21 en su biblioteca de juegos haciendo clic en la pestaña "Biblioteca" en el menú de la izquierda. Verás una lista de juegos que posees o a los que tienes acceso a través de EA Play o EA Play Pro. Puede filtrar la lista haciendo clic en el botón "Todos los juegos" en la parte superior y seleccionando "Juegos propios". También puede buscar FIFA 21 escribiendo su nombre en la barra de búsqueda en la parte superior derecha. Una vez que encuentres FIFA 21, puedes hacer clic en él para abrir su página de juego. Verás un botón que dice "Instalar" en la esquina inferior derecha. Puedes hacer clic en él para empezar a descargar e instalar FIFA 21 en tu PC. También puede cambiar la ubicación de instalación, el idioma y otros ajustes haciendo clic en el botón "Configuración" junto al botón "Instalar".
- -Si prefieres descargar FIFA 21 de Steam, debes seguir estos pasos:
- -Para acceder a Steam, necesitas tener una cuenta de Steam. Si no tienes uno, puedes crear uno gratis haciendo clic en el botón "Únete a Steam" en la esquina superior derecha del sitio web de Steam. Deberá proporcionar su dirección de correo electrónico, contraseña, país e idioma preferido. También tendrás que aceptar el Acuerdo de suscriptor de Steam y la Política de privacidad. Si ya tienes una cuenta de Steam, puedes iniciar sesión haciendo clic en el botón "Iniciar sesión" en la esquina superior derecha del sitio web. Tendrá que introducir su nombre de usuario y contraseña.
-Una vez que haya iniciado sesión, puede ir a la tienda de Steam haciendo clic en la pestaña "Almacenar" en el menú superior. Puede buscar FIFA 21 escribiendo su nombre en la barra de búsqueda en la parte superior derecha o navegando por las categorías y géneros. Verás tres ediciones de FIFA 21 disponibles para su compra: Standard Edition, Champions Edition y Ultimate Edition. Cada edición viene con diferentes características y bonificaciones, como paquetes adicionales de FUT, iconos de FUT, elementos de modo carrera y más. Puede comparar las ediciones haciendo clic en el botón "Ver detalles" debajo de cada nombre de edición. También puede ver los comentarios de los usuarios, capturas de pantalla, vídeos y requisitos del sistema desplazándose hacia abajo en la página. Una vez que haya decidido qué edición desea, puede hacer clic en el botón "Añadir al carrito" debajo del precio.
-Para descargar y jugar FIFA 21 en tu PC, necesitas tener Para descargar y jugar FIFA 21 en tu PC, necesitas tener el cliente de Steam instalado en tu sistema. El cliente de Steam es una plataforma que te permite acceder y administrar tus juegos de Steam, amigos, comunidad y más. Si aún no lo tiene, puede descargarlo de forma gratuita ejecutando el archivo de instalación que descargó en el paso anterior y siguiendo las instrucciones para completar la instalación. Si ya lo tienes, puedes saltarte este paso.
Una vez que haya instalado el cliente de Steam, debe iniciarlo e iniciar sesión en su cuenta de Steam. Puede hacer esto haciendo clic en el botón "Iniciar sesión" en la esquina superior derecha de la ventana del cliente. Deberá ingresar su nombre de usuario y contraseña. Si has activado Steam Guard, también tendrás que introducir el código de verificación que recibes en tu teléfono o correo electrónico. Una vez que hayas iniciado sesión, puedes encontrar FIFA 21 en tu biblioteca de juegos haciendo clic en la pestaña "Biblioteca" del menú superior. Verás una lista de juegos que posees o a los que tienes acceso a través de Steam. Puede filtrar la lista haciendo clic en el botón "Todos los juegos" en la parte superior y seleccionando "Juegos instalados". También puede buscar FIFA 21 escribiendo su nombre en la barra de búsqueda en la parte superior derecha. Una vez que encuentres FIFA 21, puedes hacer clic en él para abrir su página de juego. Verás un botón que dice "Instalar" en la esquina inferior derecha. Puedes hacer clic en él para empezar a descargar e instalar FIFA 21 en tu PC. También puede cambiar la ubicación de instalación, el idioma y otros ajustes haciendo clic en el botón "Configuración" junto al botón "Instalar".
-¿Te encantan los juegos de puzzle que desafían tus habilidades multitarea y creatividad? ¿Quieres crear tu propio teclado y ganar dinero colocando y fusionando botones? Si es así, entonces deberías probar Button Fever, un nuevo y emocionante juego de Rollic Games que está disponible de forma gratuita en dispositivos Android.
-Button Fever es un juego de puzzle que pone a prueba tu capacidad para gestionar varios botones a la vez. Se comienza con un teclado en blanco y unos botones de diferentes colores y formas. Su objetivo es colocar los botones en el teclado y combinarlos para crear nuevos y mejores botones que generan más monedas. Puede utilizar las monedas para comprar más botones o actualizar los existentes. El juego se vuelve más desafiante a medida que avanzas, ya que tienes que lidiar con más botones y espacio limitado en el teclado.
-Download Zip ->>->>->> https://bltlly.com/2v6M9C
El modo de juego de Button Fever es simple pero adictivo. Solo tienes que arrastrar y soltar los botones del teclado y tocarlos para recoger monedas. También puedes deslizarlos para combinarlos con otros botones del mismo color o forma. Los botones de fusión crearán nuevos botones que tendrán mayor valor y producirán más monedas. También puede actualizar sus botones gastando monedas en ellos. Los botones de actualización aumentarán su velocidad, tamaño, forma o color.
-Button Fever no es solo un juego sin sentido. También tiene algunas características interesantes que lo hacen más divertido y atractivo. Algunas de estas características son:
-y competir con otros jugadores en las tablas de clasificación globales. También puedes compartir tu progreso y logros con tus amigos en las redes sociales.
Button Fever es un juego gratuito que puedes descargar y jugar en tu dispositivo Android. Hay diferentes maneras de descargar Button Fever gratis, dependiendo de su preferencia y conveniencia. Estos son algunos de los métodos que puedes usar:
-La forma más fácil y común de descargar Button Fever es desde Google Play Store. Solo tienes que seguir estos sencillos pasos:
-Si quieres jugar Button Fever en tu PC o Mac, puedes usar un emulador de Android como BlueStacks. BlueStacks es un software que te permite ejecutar aplicaciones y juegos para Android en tu ordenador. Puedes descargar Button Fever de BlueStacks siguiendo estos pasos:
- -Otro emulador de Android que puedes usar para reproducir Button Fever en tu PC o Mac es LDPlayer. LDPlayer es un emulador ligero y rápido que admite juegos de alto rendimiento. Puedes descargar Button Fever desde LDPlayer siguiendo estos pasos:
-Si quieres tener una mejor experiencia de juego, puedes jugar Button Fever en tu PC o Mac usando un emulador de Android. Jugar Button Fever en su computadora tiene algunos beneficios que usted podría no obtener en su dispositivo móvil. Algunos de estos beneficios son:
-Si quieres jugar Button Fever en tu PC o Mac usando BlueStacks Emulator, puedes seguir estos pasos:
Si quieres jugar Button Fever en tu PC o Mac usando LDPlayer Emulator, puedes seguir estos pasos:
-Button Fever es un divertido y adictivo juego de puzzle que puedes jugar gratis en tu dispositivo Android o tu PC o Mac. Puede crear su propio teclado y ganar dinero mediante la colocación y la fusión de botones de diferentes colores y formas. También puede personalizar su teclado con diferentes temas, modos, logros y bonos. Puedes descargar Button Fever desde Google Play Store o desde un emulador de Android como BlueStacks o LDPlayer. Si te gustan los juegos de puzzle que desafían tus habilidades multitarea y creatividad, ¡deberías probar Button Fever hoy!
-Si estás listo para divertirte con los botones, ¡descarga Button Fever ahora y empieza a jugar! ¡No te arrepentirás!
-Aquí hay algunas preguntas frecuentes sobre Button Fever:
-Hay más de 100 botones de diferentes colores, formas, tamaños y valores en Button Fever. Puedes desbloquear más botones jugando el juego o comprándolos con monedas.
-Puedes obtener más monedas colocando y fusionando botones, tocándolos para recoger monedas, actualizándolos, completando tareas, girando la rueda, viendo anuncios, ingresando diariamente o comprándolos con dinero real.
-Puede cambiar el tema de su teclado yendo al menú de configuración y eligiendo entre diferentes opciones, como Neón, Arco iris, Galaxy o Candy. Cada tema tiene su propio fondo, música, efectos de sonido y diseños de botones.
-Puedes jugar Button Fever en diferentes modos yendo al menú de selección de modo y eligiendo entre diferentes opciones, como Modo Clásico, Modo Tiempo, Modo Desafío o Modo Personalizado. Cada modo tiene sus propias reglas y objetivos que requieren diferentes estrategias y habilidades.
- -Puedes disfrutar de Button Fever en una pantalla más grande, mejores controles, rendimiento más rápido y sin pérdida de batería al reproducirlo en tu PC o Mac usando un emulador de Android como BlueStacks o LDPlayer. También puede acceder a más funciones y configuraciones que no están disponibles en dispositivos móviles.
-BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks| Github Repo
" - - -gr.Interface( - fn=predict, - inputs=gr.inputs.Image(type='pil', label="Orignal"), - outputs=[ - gr.outputs.Image(type='pil', label="Low-resolution image (input to SRGAN)"), - gr.outputs.Image(type='pil', label="Super-resolved image (output of SRGAN)"), - gr.outputs.Image(type='pil', label="Alpha parameter map characterizing per-pixel distribution (output of BayesCap)"), - gr.outputs.Image(type='pil', label="Beta parameter map characterizing per-pixel distribution (output of BayesCap)"), - gr.outputs.Image(type='pil', label="Per-pixel uncertainty map (derived using outputs of BayesCap)") - ], - title=title, - description=description, - article=article, - examples=[ - ["./demo_examples/tue.jpeg"], - ["./demo_examples/baby.png"], - ["./demo_examples/bird.png"], - ["./demo_examples/butterfly.png"], - ["./demo_examples/head.png"], - ["./demo_examples/woman.png"], - ] -).launch() diff --git a/spaces/FantasticGNU/AnomalyGPT/model/ImageBind/CODE_OF_CONDUCT.md b/spaces/FantasticGNU/AnomalyGPT/model/ImageBind/CODE_OF_CONDUCT.md deleted file mode 100644 index f913b6a55a6c5ab6e1224e11fc039c3d4c3b6283..0000000000000000000000000000000000000000 --- a/spaces/FantasticGNU/AnomalyGPT/model/ImageBind/CODE_OF_CONDUCT.md +++ /dev/null @@ -1,80 +0,0 @@ -# Code of Conduct - -## Our Pledge - -In the interest of fostering an open and welcoming environment, we as -contributors and maintainers pledge to make participation in our project and -our community a harassment-free experience for everyone, regardless of age, body -size, disability, ethnicity, sex characteristics, gender identity and expression, -level of experience, education, socio-economic status, nationality, personal -appearance, race, religion, or sexual identity and orientation. - -## Our Standards - -Examples of behavior that contributes to creating a positive environment -include: - -* Using welcoming and inclusive language -* Being respectful of differing viewpoints and experiences -* Gracefully accepting constructive criticism -* Focusing on what is best for the community -* Showing empathy towards other community members - -Examples of unacceptable behavior by participants include: - -* The use of sexualized language or imagery and unwelcome sexual attention or -advances -* Trolling, insulting/derogatory comments, and personal or political attacks -* Public or private harassment -* Publishing others' private information, such as a physical or electronic -address, without explicit permission -* Other conduct which could reasonably be considered inappropriate in a -professional setting - -## Our Responsibilities - -Project maintainers are responsible for clarifying the standards of acceptable -behavior and are expected to take appropriate and fair corrective action in -response to any instances of unacceptable behavior. - -Project maintainers have the right and responsibility to remove, edit, or -reject comments, commits, code, wiki edits, issues, and other contributions -that are not aligned to this Code of Conduct, or to ban temporarily or -permanently any contributor for other behaviors that they deem inappropriate, -threatening, offensive, or harmful. - -## Scope - -This Code of Conduct applies within all project spaces, and it also applies when -an individual is representing the project or its community in public spaces. -Examples of representing a project or community include using an official -project e-mail address, posting via an official social media account, or acting -as an appointed representative at an online or offline event. Representation of -a project may be further defined and clarified by project maintainers. - -This Code of Conduct also applies outside the project spaces when there is a -reasonable belief that an individual's behavior may have a negative impact on -the project or its community. - -## Enforcement - -Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported by contacting the project team at
- Demo for Lowpoly Office Stable Diffusion model.
- {"Add the following tokens to your prompts for the model to work properly: prefix" if prefix else ""}
-
This space was created using SD Space Creator.
-Tips!!! (More detailed instructions are coming soon):
- - """ - ) - gr.Markdown( - ''' - After uploading the image, you can have a **multi-modal dialogue** by sending messages like: `what is it in the image?` or `what is the background color of image?`. - - You also can interactively operate, edit or generate the image as follows: - - You can click the image and press the button `Pick` to **visualize the segmented region** or press the button `OCR` to **recognize the words** at chosen position; - - To **remove the masked reigon** in the image, you can send the message like: `remove the maked region`; - - To **replace the masked reigon** in the image, you can send the message like: `replace the maked region with {your prompt}`; - - To **generate a new image**, you can send the message like: `generate a new image based on its segmentation decribing {your prompt}` - - To **create a new image by your scribble**, you can press button `Whiteboard` and drawing in the below board. After drawing, you need to press the button `Save` and send the message like: `generate a new image based on this scribble decribing {your prompt}`. - ''' - ) - gr.HTML( - """ - -More features is coming soon. Hope you have fun with our demo!
- - """ - ) - - if args.https: - demo.queue().launch(server_name="0.0.0.0", ssl_certfile="./certificate/cert.pem", ssl_keyfile="./certificate/key.pem", ssl_verify=False, server_port=args.port) - else: - demo.queue().launch(server_name="0.0.0.0", server_port=args.port) - diff --git a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/docs/tutorials/models.md b/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/docs/tutorials/models.md deleted file mode 100644 index 3cf918e7a145ee326c6cccf8a88835b7e02a7c30..0000000000000000000000000000000000000000 --- a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/docs/tutorials/models.md +++ /dev/null @@ -1,180 +0,0 @@ -# Use Models - -## Build Models from Yacs Config -From a yacs config object, -models (and their sub-models) can be built by -functions such as `build_model`, `build_backbone`, `build_roi_heads`: -```python -from detectron2.modeling import build_model -model = build_model(cfg) # returns a torch.nn.Module -``` - -`build_model` only builds the model structure and fills it with random parameters. -See below for how to load an existing checkpoint to the model and how to use the `model` object. - -### Load/Save a Checkpoint -```python -from detectron2.checkpoint import DetectionCheckpointer -DetectionCheckpointer(model).load(file_path_or_url) # load a file, usually from cfg.MODEL.WEIGHTS - -checkpointer = DetectionCheckpointer(model, save_dir="output") -checkpointer.save("model_999") # save to output/model_999.pth -``` - -Detectron2's checkpointer recognizes models in pytorch's `.pth` format, as well as the `.pkl` files -in our model zoo. -See [API doc](../modules/checkpoint.html#detectron2.checkpoint.DetectionCheckpointer) -for more details about its usage. - -The model files can be arbitrarily manipulated using `torch.{load,save}` for `.pth` files or -`pickle.{dump,load}` for `.pkl` files. - -### Use a Model - -A model can be called by `outputs = model(inputs)`, where `inputs` is a `list[dict]`. -Each dict corresponds to one image and the required keys -depend on the type of model, and whether the model is in training or evaluation mode. -For example, in order to do inference, -all existing models expect the "image" key, and optionally "height" and "width". -The detailed format of inputs and outputs of existing models are explained below. - -__Training__: When in training mode, all models are required to be used under an `EventStorage`. -The training statistics will be put into the storage: -```python -from detectron2.utils.events import EventStorage -with EventStorage() as storage: - losses = model(inputs) -``` - -__Inference__: If you only want to do simple inference using an existing model, -[DefaultPredictor](../modules/engine.html#detectron2.engine.defaults.DefaultPredictor) -is a wrapper around model that provides such basic functionality. -It includes default behavior including model loading, preprocessing, -and operates on single image rather than batches. See its documentation for usage. - -You can also run inference directly like this: -``` -model.eval() -with torch.no_grad(): - outputs = model(inputs) -``` - -### Model Input Format - -Users can implement custom models that support any arbitrary input format. -Here we describe the standard input format that all builtin models support in detectron2. -They all take a `list[dict]` as the inputs. Each dict -corresponds to information about one image. - -The dict may contain the following keys: - -* "image": `Tensor` in (C, H, W) format. The meaning of channels are defined by `cfg.INPUT.FORMAT`. - Image normalization, if any, will be performed inside the model using - `cfg.MODEL.PIXEL_{MEAN,STD}`. -* "height", "width": the **desired** output height and width **in inference**, which is not necessarily the same - as the height or width of the `image` field. - For example, the `image` field contains the resized image, if resize is used as a preprocessing step. - But you may want the outputs to be in **original** resolution. - If provided, the model will produce output in this resolution, - rather than in the resolution of the `image` as input into the model. This is more efficient and accurate. -* "instances": an [Instances](../modules/structures.html#detectron2.structures.Instances) - object for training, with the following fields: - + "gt_boxes": a [Boxes](../modules/structures.html#detectron2.structures.Boxes) object storing N boxes, one for each instance. - + "gt_classes": `Tensor` of long type, a vector of N labels, in range [0, num_categories). - + "gt_masks": a [PolygonMasks](../modules/structures.html#detectron2.structures.PolygonMasks) - or [BitMasks](../modules/structures.html#detectron2.structures.BitMasks) object storing N masks, one for each instance. - + "gt_keypoints": a [Keypoints](../modules/structures.html#detectron2.structures.Keypoints) - object storing N keypoint sets, one for each instance. -* "sem_seg": `Tensor[int]` in (H, W) format. The semantic segmentation ground truth for training. - Values represent category labels starting from 0. -* "proposals": an [Instances](../modules/structures.html#detectron2.structures.Instances) - object used only in Fast R-CNN style models, with the following fields: - + "proposal_boxes": a [Boxes](../modules/structures.html#detectron2.structures.Boxes) object storing P proposal boxes. - + "objectness_logits": `Tensor`, a vector of P scores, one for each proposal. - -For inference of builtin models, only "image" key is required, and "width/height" are optional. - -We currently don't define standard input format for panoptic segmentation training, -because models now use custom formats produced by custom data loaders. - -#### How it connects to data loader: - -The output of the default [DatasetMapper]( ../modules/data.html#detectron2.data.DatasetMapper) is a dict -that follows the above format. -After the data loader performs batching, it becomes `list[dict]` which the builtin models support. - - -### Model Output Format - -When in training mode, the builtin models output a `dict[str->ScalarTensor]` with all the losses. - -When in inference mode, the builtin models output a `list[dict]`, one dict for each image. -Based on the tasks the model is doing, each dict may contain the following fields: - -* "instances": [Instances](../modules/structures.html#detectron2.structures.Instances) - object with the following fields: - * "pred_boxes": [Boxes](../modules/structures.html#detectron2.structures.Boxes) object storing N boxes, one for each detected instance. - * "scores": `Tensor`, a vector of N confidence scores. - * "pred_classes": `Tensor`, a vector of N labels in range [0, num_categories). - + "pred_masks": a `Tensor` of shape (N, H, W), masks for each detected instance. - + "pred_keypoints": a `Tensor` of shape (N, num_keypoint, 3). - Each row in the last dimension is (x, y, score). Confidence scores are larger than 0. -* "sem_seg": `Tensor` of (num_categories, H, W), the semantic segmentation prediction. -* "proposals": [Instances](../modules/structures.html#detectron2.structures.Instances) - object with the following fields: - * "proposal_boxes": [Boxes](../modules/structures.html#detectron2.structures.Boxes) - object storing N boxes. - * "objectness_logits": a torch vector of N confidence scores. -* "panoptic_seg": A tuple of `(pred: Tensor, segments_info: Optional[list[dict]])`. - The `pred` tensor has shape (H, W), containing the segment id of each pixel. - - * If `segments_info` exists, each dict describes one segment id in `pred` and has the following fields: - - * "id": the segment id - * "isthing": whether the segment is a thing or stuff - * "category_id": the category id of this segment. - - If a pixel's id does not exist in `segments_info`, it is considered to be void label - defined in [Panoptic Segmentation](https://arxiv.org/abs/1801.00868). - - * If `segments_info` is None, all pixel values in `pred` must be ≥ -1. - Pixels with value -1 are assigned void labels. - Otherwise, the category id of each pixel is obtained by - `category_id = pixel // metadata.label_divisor`. - - -### Partially execute a model: - -Sometimes you may want to obtain an intermediate tensor inside a model, -such as the input of certain layer, the output before post-processing. -Since there are typically hundreds of intermediate tensors, there isn't an API that provides you -the intermediate result you need. -You have the following options: - -1. Write a (sub)model. Following the [tutorial](./write-models.md), you can - rewrite a model component (e.g. a head of a model), such that it - does the same thing as the existing component, but returns the output - you need. -2. Partially execute a model. You can create the model as usual, - but use custom code to execute it instead of its `forward()`. For example, - the following code obtains mask features before mask head. - - ```python - images = ImageList.from_tensors(...) # preprocessed input tensor - model = build_model(cfg) - model.eval() - features = model.backbone(images.tensor) - proposals, _ = model.proposal_generator(images, features) - instances, _ = model.roi_heads(images, features, proposals) - mask_features = [features[f] for f in model.roi_heads.in_features] - mask_features = model.roi_heads.mask_pooler(mask_features, [x.pred_boxes for x in instances]) - ``` - -3. Use [forward hooks](https://pytorch.org/tutorials/beginner/former_torchies/nnft_tutorial.html#forward-and-backward-function-hooks). - Forward hooks can help you obtain inputs or outputs of a certain module. - If they are not exactly what you want, they can at least be used together with partial execution - to obtain other tensors. - -All options require you to read documentation and sometimes code -of the existing models to understand the internal logic, -in order to write code to obtain the internal tensors. diff --git a/spaces/OpenMotionLab/MotionGPT/pyrender/tests/unit/test_cameras.py b/spaces/OpenMotionLab/MotionGPT/pyrender/tests/unit/test_cameras.py deleted file mode 100644 index 7544ad8f8e3ee55236fd2e32dbc12065153cbe5b..0000000000000000000000000000000000000000 --- a/spaces/OpenMotionLab/MotionGPT/pyrender/tests/unit/test_cameras.py +++ /dev/null @@ -1,164 +0,0 @@ -import numpy as np -import pytest - -from pyrender import PerspectiveCamera, OrthographicCamera - - -def test_perspective_camera(): - - # Set up constants - znear = 0.05 - zfar = 100 - yfov = np.pi / 3.0 - width = 1000.0 - height = 500.0 - aspectRatio = 640.0 / 480.0 - - # Test basics - with pytest.raises(TypeError): - p = PerspectiveCamera() - - p = PerspectiveCamera(yfov=yfov) - assert p.yfov == yfov - assert p.znear == 0.05 - assert p.zfar is None - assert p.aspectRatio is None - p.name = 'asdf' - p.name = None - - with pytest.raises(ValueError): - p.yfov = 0.0 - - with pytest.raises(ValueError): - p.yfov = -1.0 - - with pytest.raises(ValueError): - p.znear = -1.0 - - p.znear = 0.0 - p.znear = 0.05 - p.zfar = 100.0 - assert p.zfar == 100.0 - - with pytest.raises(ValueError): - p.zfar = 0.03 - - with pytest.raises(ValueError): - p.zfar = 0.05 - - p.aspectRatio = 10.0 - assert p.aspectRatio == 10.0 - - with pytest.raises(ValueError): - p.aspectRatio = 0.0 - - with pytest.raises(ValueError): - p.aspectRatio = -1.0 - - # Test matrix getting/setting - - # NF - p.znear = 0.05 - p.zfar = 100 - p.aspectRatio = None - - with pytest.raises(ValueError): - p.get_projection_matrix() - - assert np.allclose( - p.get_projection_matrix(width, height), - np.array([ - [1.0 / (width / height * np.tan(yfov / 2.0)), 0.0, 0.0, 0.0], - [0.0, 1.0 / np.tan(yfov / 2.0), 0.0, 0.0], - [0.0, 0.0, (zfar + znear) / (znear - zfar), - (2 * zfar * znear) / (znear - zfar)], - [0.0, 0.0, -1.0, 0.0] - ]) - ) - - # NFA - p.aspectRatio = aspectRatio - assert np.allclose( - p.get_projection_matrix(width, height), - np.array([ - [1.0 / (aspectRatio * np.tan(yfov / 2.0)), 0.0, 0.0, 0.0], - [0.0, 1.0 / np.tan(yfov / 2.0), 0.0, 0.0], - [0.0, 0.0, (zfar + znear) / (znear - zfar), - (2 * zfar * znear) / (znear - zfar)], - [0.0, 0.0, -1.0, 0.0] - ]) - ) - assert np.allclose( - p.get_projection_matrix(), p.get_projection_matrix(width, height) - ) - - # N - p.zfar = None - p.aspectRatio = None - assert np.allclose( - p.get_projection_matrix(width, height), - np.array([ - [1.0 / (width / height * np.tan(yfov / 2.0)), 0.0, 0.0, 0.0], - [0.0, 1.0 / np.tan(yfov / 2.0), 0.0, 0.0], - [0.0, 0.0, -1.0, -2.0 * znear], - [0.0, 0.0, -1.0, 0.0] - ]) - ) - - -def test_orthographic_camera(): - xm = 1.0 - ym = 2.0 - n = 0.05 - f = 100.0 - - with pytest.raises(TypeError): - c = OrthographicCamera() - - c = OrthographicCamera(xmag=xm, ymag=ym) - - assert c.xmag == xm - assert c.ymag == ym - assert c.znear == 0.05 - assert c.zfar == 100.0 - assert c.name is None - - with pytest.raises(TypeError): - c.ymag = None - - with pytest.raises(ValueError): - c.ymag = 0.0 - - with pytest.raises(ValueError): - c.ymag = -1.0 - - with pytest.raises(TypeError): - c.xmag = None - - with pytest.raises(ValueError): - c.xmag = 0.0 - - with pytest.raises(ValueError): - c.xmag = -1.0 - - with pytest.raises(TypeError): - c.znear = None - - with pytest.raises(ValueError): - c.znear = 0.0 - - with pytest.raises(ValueError): - c.znear = -1.0 - - with pytest.raises(ValueError): - c.zfar = 0.01 - - assert np.allclose( - c.get_projection_matrix(), - np.array([ - [1.0 / xm, 0, 0, 0], - [0, 1.0 / ym, 0, 0], - [0, 0, 2.0 / (n - f), (f + n) / (n - f)], - [0, 0, 0, 1.0] - ]) - ) diff --git a/spaces/OptimalScale/Robin-7b/lmflow/pipeline/finetuner.py b/spaces/OptimalScale/Robin-7b/lmflow/pipeline/finetuner.py deleted file mode 100644 index dff56470f76983b896e15544014d19525731b843..0000000000000000000000000000000000000000 --- a/spaces/OptimalScale/Robin-7b/lmflow/pipeline/finetuner.py +++ /dev/null @@ -1,273 +0,0 @@ -#!/usr/bin/env python -# coding=utf-8 -"""The Finetuner class simplifies the process of running finetuning process on a language model for a TunableModel instance with given dataset. -""" - -import logging -import os -import sys - -import datasets -import transformers - -from itertools import chain -from transformers import ( - Trainer, - default_data_collator, - set_seed, -) -from transformers.utils import send_example_telemetry - -from lmflow.datasets.dataset import Dataset -from lmflow.pipeline.base_tuner import BaseTuner - - -logger = logging.getLogger(__name__) - - -class Finetuner(BaseTuner): - """ - Initializes the `Finetuner` class with given arguments. - - Parameters - ------------ - model_args : ModelArguments object. - Contains the arguments required to load the model. - - data_args : DatasetArguments object. - Contains the arguments required to load the dataset. - - finetuner_args : FinetunerArguments object. - Contains the arguments required to perform finetuning. - - args : Optional. - Positional arguments. - - kwargs : Optional. - Keyword arguments. - - """ - def __init__(self, model_args, data_args, finetuner_args, *args, **kwargs): - - self.model_args = model_args - self.data_args = data_args - self.finetuner_args = finetuner_args - - # Sending telemetry. Tracking the example usage helps us better - # allocate resources to maintain them. The information sent is the one - # passed as arguments along with your Python/PyTorch versions. - send_example_telemetry("run_clm", model_args, data_args) - - # Setup logging - logging.basicConfig( - format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", - datefmt="%m/%d/%Y %H:%M:%S", - handlers=[logging.StreamHandler(sys.stdout)], - ) - - log_level = finetuner_args.get_process_log_level() - logger.setLevel(log_level) - datasets.utils.logging.set_verbosity(log_level) - transformers.utils.logging.set_verbosity(log_level) - transformers.utils.logging.enable_default_handler() - transformers.utils.logging.enable_explicit_format() - - # Log on each process the small summary: - logger.warning( - f"Process rank: {finetuner_args.local_rank}," - f" device: {finetuner_args.device}," - f" n_gpu: {finetuner_args.n_gpu}" - f"distributed training: {bool(finetuner_args.local_rank != -1)}," - f" 16-bits training: {finetuner_args.fp16}" - ) - logger.info(f"Training/evaluation parameters {finetuner_args}") - - # Detecting last checkpoint. - last_checkpoint = None - if os.path.isdir(finetuner_args.output_dir) and finetuner_args.do_train and not finetuner_args.overwrite_output_dir: - last_checkpoint = get_last_checkpoint(finetuner_args.output_dir) - if last_checkpoint is None and len(os.listdir(finetuner_args.output_dir)) > 0: - raise ValueError( - f"Output directory ({finetuner_args.output_dir}) already" - " exists and is not empty. " - "Use --overwrite_output_dir to overcome." - ) - elif last_checkpoint is not None and finetuner_args.resume_from_checkpoint is None: - logger.info( - f"Checkpoint detected, resuming training at" - f" {last_checkpoint}. To avoid this behavior, change" - " the `--output_dir` or add `--overwrite_output_dir` to" - " train from scratch." - ) - self.last_checkpoint = last_checkpoint - - # Set seed before initializing model. - set_seed(finetuner_args.seed) - - - def group_text(self, tokenized_datasets, model_max_length): - """ - Groups texts together to form blocks of maximum length `model_max_length` and returns the processed data as - a dictionary. - """ - data_args = self.data_args - finetuner_args = self.finetuner_args - - if data_args.block_size is None: - block_size = model_max_length - if block_size > 1024: - logger.warning( - "The chosen tokenizer supports a `model_max_length` that is" - " longer than the default `block_size` value" - " of 1024. If you would like to use a longer `block_size`" - " up to `tokenizer.model_max_length` you can override this " - " default with `--block_size xxx`." - ) - block_size = 1024 - else: - if data_args.block_size > model_max_length: - logger.warning( - f"The block_size passed ({data_args.block_size}) is larger" - f" than the maximum length for the model" - f"({model_max_length})." - f" Using block_size={model_max_length}." - ) - block_size = min(data_args.block_size, model_max_length) - - # Main data processing function that will concatenate all texts from - # our dataset and generate chunks of block_size. - def group_texts(examples): - # Concatenate all texts. - concatenated_examples = {k: list(chain(*examples[k])) for k in examples.keys()} - total_length = len(concatenated_examples[list(examples.keys())[0]]) - # We drop the small remainder, we could add padding if the model - # supported it instead of this drop, you can customize this part to - # your needs. - total_length = (total_length // block_size) * block_size - # Split by chunks of max_len. - result = { - k: [t[i : i + block_size] for i in range(0, total_length, block_size)] - for k, t in concatenated_examples.items() - } - return result - - # Note that with `batched=True`, this map processes 1,000 texts - # together, so group_texts throws away a remainder for each of those - # groups of 1,000 texts. You can adjust that batch_size here but a - # higher value might be slower to preprocess. - # - # To speed up this part, we use multiprocessing. See the documentation - # of the map method for more information: - # https://huggingface.co/docs/datasets/package_reference/main_classes.html#datasets.Dataset.map - with finetuner_args.main_process_first(desc="grouping texts together"): - group_batch_size = 1000 - if data_args.disable_group_texts: - group_batch_size = 1 - if not data_args.streaming: - lm_datasets = tokenized_datasets.map( - group_texts, - batched=True, - batch_size=group_batch_size, - num_proc=data_args.preprocessing_num_workers, - load_from_cache_file=not data_args.overwrite_cache, - desc=f"Grouping texts in chunks of {block_size}", - ) - else: - lm_datasets = tokenized_datasets.map( - group_texts, - batched=True, - batch_size=group_batch_size, - ) - - return lm_datasets - - - def tune(self, model, dataset): - """ - Perform tuning for a model - - Parameters - ------------ - model : TunableModel object. - TunableModel to perform tuning. - - dataset: - dataset to train model. - - """ - model_args = self.model_args - data_args = self.data_args - finetuner_args = self.finetuner_args - - # Tokenization and text grouping must be done in the main process - with finetuner_args.main_process_first(desc="dataset map tokenization"): - tokenized_dataset = model.tokenize(dataset) - lm_dataset = self.group_text( - tokenized_dataset, - model_max_length=model.get_max_length(), - ) - - train_dataset = lm_dataset.get_backend_dataset() - - if finetuner_args.do_train: - if data_args.max_train_samples is not None: - max_train_samples = min(len(train_dataset), data_args.max_train_samples) - train_dataset = train_dataset.select(range(max_train_samples)) - - # Initialize our Trainer - training_args = finetuner_args - trainer = Trainer( - model=model.get_backend_model(), - args=training_args, - train_dataset=train_dataset if training_args.do_train else None, - eval_dataset=None, - tokenizer=model.get_tokenizer(), - # Data collator will default to DataCollatorWithPadding, so we change it. - data_collator=default_data_collator, - compute_metrics=None, - preprocess_logits_for_metrics=None, - ) - - # Training - if training_args.do_train: - checkpoint = None - last_checkpoint = self.last_checkpoint - if training_args.resume_from_checkpoint is not None: - checkpoint = training_args.resume_from_checkpoint - elif last_checkpoint is not None: - checkpoint = last_checkpoint - train_result = trainer.train(resume_from_checkpoint=checkpoint) - - if not model_args.use_lora: - trainer.save_model() # Saves the tokenizer too for easy upload - else: - if model_args.save_aggregated_lora: - model.merge_lora_weights() - model.save(finetuner_args.output_dir,model_args.save_aggregated_lora) - - metrics = train_result.metrics - - max_train_samples = ( - data_args.max_train_samples if data_args.max_train_samples is not None else len(train_dataset) - ) - metrics["train_samples"] = min(max_train_samples, len(train_dataset)) - - trainer.log_metrics("train", metrics) - trainer.save_metrics("train", metrics) - trainer.save_state() - - kwargs = {"finetuned_from": model_args.model_name_or_path, "tasks": "text-generation"} - if data_args.dataset_name is not None: - kwargs["dataset_tags"] = data_args.dataset_name - if data_args.dataset_config_name is not None: - kwargs["dataset_args"] = data_args.dataset_config_name - kwargs["dataset"] = f"{data_args.dataset_name} {data_args.dataset_config_name}" - else: - kwargs["dataset"] = data_args.dataset_name - - if training_args.push_to_hub: - trainer.push_to_hub(**kwargs) - else: - trainer.create_model_card(**kwargs) - - return model diff --git a/spaces/PAIR/Text2Video-Zero/annotator/uniformer/mmcv/ops/deform_roi_pool.py b/spaces/PAIR/Text2Video-Zero/annotator/uniformer/mmcv/ops/deform_roi_pool.py deleted file mode 100644 index cc245ba91fee252226ba22e76bb94a35db9a629b..0000000000000000000000000000000000000000 --- a/spaces/PAIR/Text2Video-Zero/annotator/uniformer/mmcv/ops/deform_roi_pool.py +++ /dev/null @@ -1,204 +0,0 @@ -# Copyright (c) OpenMMLab. All rights reserved. -from torch import nn -from torch.autograd import Function -from torch.autograd.function import once_differentiable -from torch.nn.modules.utils import _pair - -from ..utils import ext_loader - -ext_module = ext_loader.load_ext( - '_ext', ['deform_roi_pool_forward', 'deform_roi_pool_backward']) - - -class DeformRoIPoolFunction(Function): - - @staticmethod - def symbolic(g, input, rois, offset, output_size, spatial_scale, - sampling_ratio, gamma): - return g.op( - 'mmcv::MMCVDeformRoIPool', - input, - rois, - offset, - pooled_height_i=output_size[0], - pooled_width_i=output_size[1], - spatial_scale_f=spatial_scale, - sampling_ratio_f=sampling_ratio, - gamma_f=gamma) - - @staticmethod - def forward(ctx, - input, - rois, - offset, - output_size, - spatial_scale=1.0, - sampling_ratio=0, - gamma=0.1): - if offset is None: - offset = input.new_zeros(0) - ctx.output_size = _pair(output_size) - ctx.spatial_scale = float(spatial_scale) - ctx.sampling_ratio = int(sampling_ratio) - ctx.gamma = float(gamma) - - assert rois.size(1) == 5, 'RoI must be (idx, x1, y1, x2, y2)!' - - output_shape = (rois.size(0), input.size(1), ctx.output_size[0], - ctx.output_size[1]) - output = input.new_zeros(output_shape) - - ext_module.deform_roi_pool_forward( - input, - rois, - offset, - output, - pooled_height=ctx.output_size[0], - pooled_width=ctx.output_size[1], - spatial_scale=ctx.spatial_scale, - sampling_ratio=ctx.sampling_ratio, - gamma=ctx.gamma) - - ctx.save_for_backward(input, rois, offset) - return output - - @staticmethod - @once_differentiable - def backward(ctx, grad_output): - input, rois, offset = ctx.saved_tensors - grad_input = grad_output.new_zeros(input.shape) - grad_offset = grad_output.new_zeros(offset.shape) - - ext_module.deform_roi_pool_backward( - grad_output, - input, - rois, - offset, - grad_input, - grad_offset, - pooled_height=ctx.output_size[0], - pooled_width=ctx.output_size[1], - spatial_scale=ctx.spatial_scale, - sampling_ratio=ctx.sampling_ratio, - gamma=ctx.gamma) - if grad_offset.numel() == 0: - grad_offset = None - return grad_input, None, grad_offset, None, None, None, None - - -deform_roi_pool = DeformRoIPoolFunction.apply - - -class DeformRoIPool(nn.Module): - - def __init__(self, - output_size, - spatial_scale=1.0, - sampling_ratio=0, - gamma=0.1): - super(DeformRoIPool, self).__init__() - self.output_size = _pair(output_size) - self.spatial_scale = float(spatial_scale) - self.sampling_ratio = int(sampling_ratio) - self.gamma = float(gamma) - - def forward(self, input, rois, offset=None): - return deform_roi_pool(input, rois, offset, self.output_size, - self.spatial_scale, self.sampling_ratio, - self.gamma) - - -class DeformRoIPoolPack(DeformRoIPool): - - def __init__(self, - output_size, - output_channels, - deform_fc_channels=1024, - spatial_scale=1.0, - sampling_ratio=0, - gamma=0.1): - super(DeformRoIPoolPack, self).__init__(output_size, spatial_scale, - sampling_ratio, gamma) - - self.output_channels = output_channels - self.deform_fc_channels = deform_fc_channels - - self.offset_fc = nn.Sequential( - nn.Linear( - self.output_size[0] * self.output_size[1] * - self.output_channels, self.deform_fc_channels), - nn.ReLU(inplace=True), - nn.Linear(self.deform_fc_channels, self.deform_fc_channels), - nn.ReLU(inplace=True), - nn.Linear(self.deform_fc_channels, - self.output_size[0] * self.output_size[1] * 2)) - self.offset_fc[-1].weight.data.zero_() - self.offset_fc[-1].bias.data.zero_() - - def forward(self, input, rois): - assert input.size(1) == self.output_channels - x = deform_roi_pool(input, rois, None, self.output_size, - self.spatial_scale, self.sampling_ratio, - self.gamma) - rois_num = rois.size(0) - offset = self.offset_fc(x.view(rois_num, -1)) - offset = offset.view(rois_num, 2, self.output_size[0], - self.output_size[1]) - return deform_roi_pool(input, rois, offset, self.output_size, - self.spatial_scale, self.sampling_ratio, - self.gamma) - - -class ModulatedDeformRoIPoolPack(DeformRoIPool): - - def __init__(self, - output_size, - output_channels, - deform_fc_channels=1024, - spatial_scale=1.0, - sampling_ratio=0, - gamma=0.1): - super(ModulatedDeformRoIPoolPack, - self).__init__(output_size, spatial_scale, sampling_ratio, gamma) - - self.output_channels = output_channels - self.deform_fc_channels = deform_fc_channels - - self.offset_fc = nn.Sequential( - nn.Linear( - self.output_size[0] * self.output_size[1] * - self.output_channels, self.deform_fc_channels), - nn.ReLU(inplace=True), - nn.Linear(self.deform_fc_channels, self.deform_fc_channels), - nn.ReLU(inplace=True), - nn.Linear(self.deform_fc_channels, - self.output_size[0] * self.output_size[1] * 2)) - self.offset_fc[-1].weight.data.zero_() - self.offset_fc[-1].bias.data.zero_() - - self.mask_fc = nn.Sequential( - nn.Linear( - self.output_size[0] * self.output_size[1] * - self.output_channels, self.deform_fc_channels), - nn.ReLU(inplace=True), - nn.Linear(self.deform_fc_channels, - self.output_size[0] * self.output_size[1] * 1), - nn.Sigmoid()) - self.mask_fc[2].weight.data.zero_() - self.mask_fc[2].bias.data.zero_() - - def forward(self, input, rois): - assert input.size(1) == self.output_channels - x = deform_roi_pool(input, rois, None, self.output_size, - self.spatial_scale, self.sampling_ratio, - self.gamma) - rois_num = rois.size(0) - offset = self.offset_fc(x.view(rois_num, -1)) - offset = offset.view(rois_num, 2, self.output_size[0], - self.output_size[1]) - mask = self.mask_fc(x.view(rois_num, -1)) - mask = mask.view(rois_num, 1, self.output_size[0], self.output_size[1]) - d = deform_roi_pool(input, rois, offset, self.output_size, - self.spatial_scale, self.sampling_ratio, - self.gamma) - return d * mask diff --git a/spaces/PSLD/PSLD/diffusion-posterior-sampling/data/dataloader.py b/spaces/PSLD/PSLD/diffusion-posterior-sampling/data/dataloader.py deleted file mode 100644 index 47b914a0e6ec5211da4dd0461f41eb09dd5423ca..0000000000000000000000000000000000000000 --- a/spaces/PSLD/PSLD/diffusion-posterior-sampling/data/dataloader.py +++ /dev/null @@ -1,55 +0,0 @@ -from glob import glob -from PIL import Image -from typing import Callable, Optional -from torch.utils.data import DataLoader -from torchvision.datasets import VisionDataset - - -__DATASET__ = {} - -def register_dataset(name: str): - def wrapper(cls): - if __DATASET__.get(name, None): - raise NameError(f"Name {name} is already registered!") - __DATASET__[name] = cls - return cls - return wrapper - - -def get_dataset(name: str, root: str, **kwargs): - if __DATASET__.get(name, None) is None: - raise NameError(f"Dataset {name} is not defined.") - return __DATASET__[name](root=root, **kwargs) - - -def get_dataloader(dataset: VisionDataset, - batch_size: int, - num_workers: int, - train: bool): - dataloader = DataLoader(dataset, - batch_size, - shuffle=train, - num_workers=num_workers, - drop_last=train) - return dataloader - - -@register_dataset(name='ffhq') -class FFHQDataset(VisionDataset): - def __init__(self, root: str, transforms: Optional[Callable]=None): - super().__init__(root, transforms) - - self.fpaths = sorted(glob(root + '/**/*.png', recursive=True)) - assert len(self.fpaths) > 0, "File list is empty. Check the root." - - def __len__(self): - return len(self.fpaths) - - def __getitem__(self, index: int): - fpath = self.fpaths[index] - img = Image.open(fpath).convert('RGB') - - if self.transforms is not None: - img = self.transforms(img) - - return img \ No newline at end of file diff --git a/spaces/Pengyey/bingo-chuchu/src/app/layout.tsx b/spaces/Pengyey/bingo-chuchu/src/app/layout.tsx deleted file mode 100644 index 8b5122759987177b8dc4e4356d1d06cea25c15ea..0000000000000000000000000000000000000000 --- a/spaces/Pengyey/bingo-chuchu/src/app/layout.tsx +++ /dev/null @@ -1,47 +0,0 @@ -import { Metadata } from 'next' -import { Toaster } from 'react-hot-toast' -import { TailwindIndicator } from '@/components/tailwind-indicator' -import { Providers } from '@/components/providers' -import { Header } from '@/components/header' - -import '@/app/globals.scss' - - -export const metadata: Metadata = { - title: { - default: 'Bing AI Chatbot', - template: `%s - Bing AI Chatbot` - }, - description: 'Bing AI Chatbot Web App.', - themeColor: [ - { media: '(prefers-color-scheme: light)', color: 'white' }, - { media: '(prefers-color-scheme: dark)', color: 'dark' } - ], - icons: { - icon: '/favicon.ico', - shortcut: '../assets/images/logo.svg', - apple: '../assets/images/logo.svg' - } -} - -interface RootLayoutProps { - children: React.ReactNode -} - -export default function RootLayout({ children }: RootLayoutProps) { - return ( - - -Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|
R50-C4 | -1x | -0.551 | -0.102 | -4.8 | -35.7 | -137257644 | -model | metrics | -
R50-DC5 | -1x | -0.380 | -0.068 | -5.0 | -37.3 | -137847829 | -model | metrics | -
R50-FPN | -1x | -0.210 | -0.038 | -3.0 | -37.9 | -137257794 | -model | metrics | -
R50-C4 | -3x | -0.543 | -0.104 | -4.8 | -38.4 | -137849393 | -model | metrics | -
R50-DC5 | -3x | -0.378 | -0.070 | -5.0 | -39.0 | -137849425 | -model | metrics | -
R50-FPN | -3x | -0.209 | -0.038 | -3.0 | -40.2 | -137849458 | -model | metrics | -
R101-C4 | -3x | -0.619 | -0.139 | -5.9 | -41.1 | -138204752 | -model | metrics | -
R101-DC5 | -3x | -0.452 | -0.086 | -6.1 | -40.6 | -138204841 | -model | metrics | -
R101-FPN | -3x | -0.286 | -0.051 | -4.1 | -42.0 | -137851257 | -model | metrics | -
X101-FPN | -3x | -0.638 | -0.098 | -6.7 | -43.0 | -139173657 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|
R50 | -1x | -0.205 | -0.041 | -4.1 | -37.4 | -190397773 | -model | metrics | -
R50 | -3x | -0.205 | -0.041 | -4.1 | -38.7 | -190397829 | -model | metrics | -
R101 | -3x | -0.291 | -0.054 | -5.2 | -40.4 | -190397697 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-prop. AR |
-model id | -download | - - -
---|---|---|---|---|---|---|---|---|
RPN R50-C4 | -1x | -0.130 | -0.034 | -1.5 | -- | 51.6 | -137258005 | -model | metrics | -
RPN R50-FPN | -1x | -0.186 | -0.032 | -2.7 | -- | 58.0 | -137258492 | -model | metrics | -
Fast R-CNN R50-FPN | -1x | -0.140 | -0.029 | -2.6 | -37.8 | -- | 137635226 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-mask AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|---|
R50-C4 | -1x | -0.584 | -0.110 | -5.2 | -36.8 | -32.2 | -137259246 | -model | metrics | -
R50-DC5 | -1x | -0.471 | -0.076 | -6.5 | -38.3 | -34.2 | -137260150 | -model | metrics | -
R50-FPN | -1x | -0.261 | -0.043 | -3.4 | -38.6 | -35.2 | -137260431 | -model | metrics | -
R50-C4 | -3x | -0.575 | -0.111 | -5.2 | -39.8 | -34.4 | -137849525 | -model | metrics | -
R50-DC5 | -3x | -0.470 | -0.076 | -6.5 | -40.0 | -35.9 | -137849551 | -model | metrics | -
R50-FPN | -3x | -0.261 | -0.043 | -3.4 | -41.0 | -37.2 | -137849600 | -model | metrics | -
R101-C4 | -3x | -0.652 | -0.145 | -6.3 | -42.6 | -36.7 | -138363239 | -model | metrics | -
R101-DC5 | -3x | -0.545 | -0.092 | -7.6 | -41.9 | -37.3 | -138363294 | -model | metrics | -
R101-FPN | -3x | -0.340 | -0.056 | -4.6 | -42.9 | -38.6 | -138205316 | -model | metrics | -
X101-FPN | -3x | -0.690 | -0.103 | -7.2 | -44.3 | -39.5 | -139653917 | -model | metrics | -
Name | -epochs | -train time (s/im) |
-inference time (s/im) |
-box AP |
-mask AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|
R50-FPN | -100 | -0.376 | -0.069 | -44.6 | -40.3 | -42047764 | -model | metrics | -
R50-FPN | -200 | -0.376 | -0.069 | -46.3 | -41.7 | -42047638 | -model | metrics | -
R50-FPN | -400 | -0.376 | -0.069 | -47.4 | -42.5 | -42019571 | -model | metrics | -
R101-FPN | -100 | -0.518 | -0.073 | -46.4 | -41.6 | -42025812 | -model | metrics | -
R101-FPN | -200 | -0.518 | -0.073 | -48.0 | -43.1 | -42131867 | -model | metrics | -
R101-FPN | -400 | -0.518 | -0.073 | -48.9 | -43.7 | -42073830 | -model | metrics | -
regnetx_4gf_dds_FPN | -100 | -0.474 | -0.071 | -46.0 | -41.3 | -42047771 | -model | metrics | -
regnetx_4gf_dds_FPN | -200 | -0.474 | -0.071 | -48.1 | -43.1 | -42132721 | -model | metrics | -
regnetx_4gf_dds_FPN | -400 | -0.474 | -0.071 | -48.6 | -43.5 | -42025447 | -model | metrics | -
regnety_4gf_dds_FPN | -100 | -0.487 | -0.073 | -46.1 | -41.6 | -42047784 | -model | metrics | -
regnety_4gf_dds_FPN | -200 | -0.487 | -0.072 | -47.8 | -43.0 | -42047642 | -model | metrics | -
regnety_4gf_dds_FPN | -400 | -0.487 | -0.072 | -48.2 | -43.3 | -42045954 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-kp. AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|---|
R50-FPN | -1x | -0.315 | -0.072 | -5.0 | -53.6 | -64.0 | -137261548 | -model | metrics | -
R50-FPN | -3x | -0.316 | -0.066 | -5.0 | -55.4 | -65.5 | -137849621 | -model | metrics | -
R101-FPN | -3x | -0.390 | -0.076 | -6.1 | -56.4 | -66.1 | -138363331 | -model | metrics | -
X101-FPN | -3x | -0.738 | -0.121 | -8.7 | -57.3 | -66.0 | -139686956 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-mask AP |
-PQ | -model id | -download | - - -
---|---|---|---|---|---|---|---|---|---|
R50-FPN | -1x | -0.304 | -0.053 | -4.8 | -37.6 | -34.7 | -39.4 | -139514544 | -model | metrics | -
R50-FPN | -3x | -0.302 | -0.053 | -4.8 | -40.0 | -36.5 | -41.5 | -139514569 | -model | metrics | -
R101-FPN | -3x | -0.392 | -0.066 | -6.0 | -42.4 | -38.5 | -43.0 | -139514519 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-mask AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|---|
R50-FPN | -1x | -0.292 | -0.107 | -7.1 | -23.6 | -24.4 | -144219072 | -model | metrics | -
R101-FPN | -1x | -0.371 | -0.114 | -7.8 | -25.6 | -25.9 | -144219035 | -model | metrics | -
X101-FPN | -1x | -0.712 | -0.151 | -10.2 | -26.7 | -27.1 | -144219108 | -model | metrics | -
Name | -train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-box AP50 |
-mask AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|---|
R50-FPN, Cityscapes | -0.240 | -0.078 | -4.4 | -- | - | 36.5 | -142423278 | -model | metrics | -
R50-C4, VOC | -0.537 | -0.081 | -4.8 | -51.9 | -80.3 | -- | 142202221 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-mask AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|---|
Baseline R50-FPN | -1x | -0.261 | -0.043 | -3.4 | -38.6 | -35.2 | -137260431 | -model | metrics | -
Deformable Conv | -1x | -0.342 | -0.048 | -3.5 | -41.5 | -37.5 | -138602867 | -model | metrics | -
Cascade R-CNN | -1x | -0.317 | -0.052 | -4.0 | -42.1 | -36.4 | -138602847 | -model | metrics | -
Baseline R50-FPN | -3x | -0.261 | -0.043 | -3.4 | -41.0 | -37.2 | -137849600 | -model | metrics | -
Deformable Conv | -3x | -0.349 | -0.047 | -3.5 | -42.7 | -38.5 | -144998336 | -model | metrics | -
Cascade R-CNN | -3x | -0.328 | -0.053 | -4.0 | -44.3 | -38.5 | -144998488 | -model | metrics | -
Name | -lr sched |
-train time (s/iter) |
-inference time (s/im) |
-train mem (GB) |
-box AP |
-mask AP |
-model id | -download | - - -
---|---|---|---|---|---|---|---|---|
Baseline R50-FPN | -3x | -0.261 | -0.043 | -3.4 | -41.0 | -37.2 | -137849600 | -model | metrics | -
GN | -3x | -0.309 | -0.060 | -5.6 | -42.6 | -38.6 | -138602888 | -model | metrics | -
SyncBN | -3x | -0.345 | -0.053 | -5.5 | -41.9 | -37.8 | -169527823 | -model | metrics | -
GN (from scratch) | -3x | -0.338 | -0.061 | -7.2 | -39.9 | -36.6 | -138602908 | -model | metrics | -
GN (from scratch) | -9x | -N/A | -0.061 | -7.2 | -43.7 | -39.6 | -183808979 | -model | metrics | -
SyncBN (from scratch) | -9x | -N/A | -0.055 | -7.2 | -43.6 | -39.3 | -184226666 | -model | metrics | -
Name | -inference time (s/im) |
-train mem (GB) |
-box AP |
-mask AP |
-PQ | -model id | -download | - - -
---|---|---|---|---|---|---|---|
Panoptic FPN R101 | -0.098 | -11.4 | -47.4 | -41.3 | -46.1 | -139797668 | -model | metrics | -
Mask R-CNN X152 | -0.234 | -15.1 | -50.2 | -44.0 | -- | 18131413 | -model | metrics | -
above + test-time aug. | -- | - | 51.9 | -45.9 | -- | - | - |
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¿Te gustan los juegos de acción multijugador donde tienes que competir contra otros jugadores y superar todo tipo de obstáculos? ¿Te gustaría probar uno de los juegos más divertidos y populares del momento? Si tu respuesta es sí, entonces te interesará saber más sobre la primera versión de Stumble Guys APK, un juego que te hará pasar momentos increíbles en tu dispositivo Android.
-Stumble Guys es un juego de acción multijugador donde tienes que entrar en batallas con hasta 32 jugadores y ser el último en quedar en pie. Para ello, tendrás que superar todo tipo de desafíos diferentes, como correr, saltar, esquivar y empujar a tus rivales. El juego está inspirado en el famoso Fall Guys, un juego similar que se lanzó para PC y consolas en 2020.
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Stumble Guys es un juego gratuito que puedes descargar e instalar en tu dispositivo Android desde Google Play o desde otros sitios web. El juego tiene unos gráficos coloridos y simpáticos, una música animada y unos efectos de sonido divertidos. Además, el juego tiene un control sencillo e intuitivo que te permite moverte con facilidad por los esc
Stumble Guys tiene diferentes modos de juego que te ofrecen distintas experiencias. Por ejemplo, puedes jugar en el modo clásico, donde tienes que superar varias rondas hasta llegar a la final, o en el modo personalizado, donde puedes crear tu propia sala y jugar con tus amigos. Además, el juego tiene más de 30 niveles diferentes, cada uno con sus propios obstáculos y sorpresas. Nunca te aburrirás de jugar a Stumble Guys.
-La primera versión de Stumble Guys APK es una versión antigua del juego que se lanzó en agosto de 2020. Esta versión fue la primera que se publicó para Android y la que inició el éxito del juego. En esta versión, el juego tenía menos niveles, menos personajes y menos opciones que las versiones posteriores. Sin embargo, también tenía su encanto y su diversión.
-La primera versión de Stumble Guys APK tiene algunas diferencias con la versión actual del juego. Por ejemplo, en la primera versión, el juego tenía un límite de 16 jugadores por partida, mientras que en la actual hay hasta 32. También, en la primera versión, el juego tenía menos skins y accesorios para personalizar a tu personaje, mientras que en la actual hay más de 100. Además, en la primera versión, el juego tenía algunos bugs y errores que se fueron solucionando en las actualizaciones.
-La primera versión de Stumble Guys APK se puede descargar e instalar fácilmente en tu dispositivo Android. Solo tienes que buscar el archivo APK en algún sitio web confiable y seguir los pasos para instalarlo. No necesitas tener una cuenta de Google Play ni una conexión a internet para jugar. Solo necesitas tener espacio suficiente en tu memoria y ganas de divertirte.
-Una razón para descargar la primera versión de Stumble Guys APK es para probar el juego antes de que se hiciera popular. Así podrás ver cómo era el juego cuando recién salió y cómo ha evolucionado con el tiempo. También podrás sentirte como un pionero o un veterano del juego y presumir de ello ante tus amigos.
-Otra razón para descargar la primera versión de Stumble Guys APK es para disfrutar de un juego más simple y menos exigente. Al tener menos niveles, menos jugadores y menos opciones, el juego es más fácil de jugar y menos estresante. Además, al tener menos gráficos y efectos, el juego consume menos recursos y batería de tu dispositivo. Si quieres un juego más relajado y sencillo, esta versión es para ti.
-Una última razón para descargar la primera versión de Stumble Guys APK es para comparar el juego con las versiones posteriores. Así podrás ver las diferencias entre las versiones y apreciar las mejoras que se han hecho. También podrás dar tu opinión sobre qué versión te gusta más y por qué. Si eres un fanático del juego, te gustará ver cómo ha cambiado con el tiempo.
-El primer paso para descargar e instalar la primera versión de Stumble Guys APK es buscar el archivo APK en sitios web confiables. Hay muchos sitios web que ofrecen este archivo, pero no todos son seguros ni legales. Por eso, te recomendamos que busques en sitios web que tengan buena reputación y comentarios positivos. Algunos ejemplos son APKPure, Uptodown o Aptoide.
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El segundo paso para descargar e instalar la primera versión de Stumble Guys APK es permitir la instalación de fuentes desconocidas en el dispositivo.
Para instalar el archivo APK, necesitas habilitar la opción de fuentes desconocidas en tu dispositivo. Esta opción te permite instalar aplicaciones que no provienen de Google Play. Para hacerlo, debes ir a los ajustes de tu dispositivo, luego a seguridad y privacidad, y luego activar la opción de fuentes desconocidas. Si tienes una versión más reciente de Android, puedes hacerlo directamente desde el navegador cuando descargues el archivo.
-El último paso para descargar e instalar la primera versión de Stumble Guys APK es seguir los pasos del instalador y abrir el juego. Una vez que hayas descargado el archivo APK, debes abrirlo y seguir las instrucciones que aparecen en la pantalla. El proceso es muy sencillo y rápido. Cuando termine, podrás abrir el juego y empezar a jugar.
-La primera versión de Stumble Guys APK es una versión antigua del juego que se lanzó en 2020. Es una versión que tiene algunas diferencias con la actual, como menos niveles, menos jugadores y menos opciones. Sin embargo, también tiene sus ventajas, como ser más simple, menos exigente y más original. Si quieres probar el juego antes de que se hiciera popular, disfrutar de un juego más relajado o comparar el juego con las versiones posteriores, puedes descargar e instalar la primera versión de Stumble Guys APK siguiendo los pasos que te hemos explicado. Te aseguramos que te divertirás mucho con este juego de acción multijugador inspirado en Fall Guys.
-Para jugar a la primera versión de Stumble Guys APK, tu dispositivo necesita tener al menos Android 5.0, 1 GB de RAM y 100 MB de espacio libre.
-Sí, puedes jugar online con otros jugadores en la primera versión de Stumble Guys APK. Sin embargo, ten en cuenta que el número máximo de jugadores por partida es 16 y que puede haber menos personas jugando a esta versión que a la actual.
-No, no puedes actualizar la primera versión de Stumble Guys APK a la versión actual. Si quieres jugar a la versión actual, debes descargarla e instalarla desde Google Play o desde otro sitio web confiable.
-Sí, puedes personalizar a tu personaje en la primera versión de Stumble Guys APK. Sin embargo, ten en cuenta que hay menos skins y accesorios disponibles que en la versión actual.
-Sí, es seguro descargar e instalar la primera versión de Stumble Guys APK si lo haces desde sitios web confiables y si permites la instalación de fuentes desconocidas en tu dispositivo. No obstante, te recomendamos que tengas un antivirus instalado y que no compartas tus datos personales con nadie.
197e85843dIf you are a fan of romance novels, you might be interested in finding and downloading free love PDFs online. PDFs are portable document format files that can be read on any device with a PDF reader app. They are convenient, easy to store, and often cheaper than printed books. But where can you find free love PDFs? And how can you make the most of your reading experience? In this article, we will answer these questions and more. Here is the outline of the article:
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Heading | -Subheading | -
---|---|
Why Read Love PDFs? |
-The Benefits of Reading Romance Novels |
-
- | The Advantages of PDF Format |
-
Where to Find Free Love PDFs? |
-Online Libraries and Archives |
-
- | Romance eBook Websites and Blogs |
-
- | Social Media and Online Communities |
-
How to Download and Read Love PDFs? |
-Choosing a PDF Reader App |
-
- | Downloading and Saving PDF Files |
-
- | Adjusting the Reading Settings |
-
How to Enhance Your Love PDF Experience? |
-Creating a Reading List and Schedule |
-
- | Sharing Your Thoughts and Reviews |
-
- | Exploring Related Genres and Authors |
-
Conclusion |
- - |
Frequently Asked Questions (FAQs) |
- - |
Now that we have the outline, let's start writing the article based on it.
-Love PDFs are digital books that contain stories about romance, relationships, and emotions. They are popular among readers who enjoy escaping into fictional worlds where love conquers all. But reading love PDFs is not only fun, but also beneficial for your well-being. Here are some reasons why you should read love PDFs:
-According to various studies, reading romance novels can have positive effects on your mental and physical health. Some of these benefits are:
-Now that you know why you should read love PDFs and how to read them in PDF format, you might be wondering where to find them for free. There are many online sources that offer free love PDFs for download or online reading. Here are some of them:
-Online libraries and archives are websites that store and provide access to digital books, including love PDFs. Some of these websites are:
-Romance eBook websites and blogs are online platforms that specialize in publishing and reviewing romance novels, including love PDFs. Some of these websites and blogs are:
-Social media and online communities are websites and apps that allow you to connect and interact with other people who share your interests, such as reading love PDFs. Some of these websites and apps are:
-Once you have found some love PDFs that you want to read, you need to download and read them on your device. This is a simple and straightforward process, but there are some tips and tricks that can make it easier and more enjoyable. Here are some steps to follow:
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The first thing you need to do is to choose a PDF reader app that suits your needs and preferences. There are many PDF reader apps available for different devices and platforms, such as Adobe Acrobat Reader, Google Play Books, iBooks, Kindle, and Kobo. Some of the features that you should look for in a PDF reader app are:
-The next thing you need to do is to download and save the love PDFs that you want to read. Depending on the source of the love PDFs, there are different ways to do this. Here are some common methods:
-The last thing you need to do is to adjust the reading settings of your PDF reader app to make your reading experience more comfortable and enjoyable. You can customize various aspects of your reading settings, such as:
-Reading love PDFs can be a fun and rewarding activity, but you can also enhance your love PDF experience by doing some extra things. Here are some suggestions on how to make your love PDF experience more enjoyable and meaningful:
-One way to enhance your love PDF experience is to create a reading list and schedule for yourself. You can choose the love PDFs that you want to read based on your interests, preferences, and goals. You can also set a reading schedule for yourself, such as how many pages or chapters you want to read per day or week. This can help you stay organized, motivated, and focused on your reading.
-Another way to enhance your love PDF experience is to share your thoughts and reviews with others. You can write your own reviews of the love PDFs that you have read and post them on online platforms, such as Goodreads, Amazon, or your own blog. You can also read other people's reviews and comments and join the discussion. This can help you express your opinions, learn from others, and discover new love PDFs.
-A third way to enhance your love PDF experience is to explore related genres and authors. You can expand your reading horizons by trying out different genres of romance novels, such as historical, paranormal, erotic, or LGBTQ+. You can also explore different authors of romance novels, such as Nora Roberts, Nicholas Sparks, or E.L. James. This can help you diversify your reading taste, find new favorites, and appreciate different styles and perspectives.
-In conclusion, reading love PDFs is a great way to enjoy romance novels in a convenient, easy, and cheap way. You can find free love PDFs from various online sources, download and read them on any device with a PDF reader app, and enhance your love PDF experience by creating a reading list and schedule, sharing your thoughts and reviews, and exploring related genres and authors. If you are a fan of romance novels or want to try something new, why not give love PDFs a try? You might be surprised by how much you will love them!
-Here are some FAQs that you might have about reading love PDFs:
-Some tips for finding good quality love PDFs are:
-If you have romance eBooks in other file formats, such as EPUB or MOBI, you can convert them into PDF format using online tools or apps, such as Zamzar, Online-Convert, or Calibre.
-If you want to print your love PDFs, you can do so using your printer or a printing service. You can also use online tools or apps, such as PrintFriendly or Adobe Acrobat Reader, to optimize your love PDFs for printing.
-If you want to support your favorite romance authors, you can do so by:
-This is a subjective question, as different readers might have different tastes and preferences. However, some of the best love PDFs to read according to popular opinion are:
-I hope you enjoyed reading this article and learned something new. If you have any questions or feedback, please feel free to leave a comment below. Happy reading!
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HDD: 3 GB free space | HDD: 3 GB free space |
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Dota 2 is the official sequel to Dota 1, which was developed by Valve Corporation and released in 2013. Dota 2 has many similarities with Dota 1, such as the same heroes, items, and maps. However, Dota 2 also has many differences from Dota 1, such as:
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- - A large and diverse cast of characters: Tekken 3 features 23 playable characters, each with their own unique moves, combos, and styles. Some of them are returning from previous games, such as Jin Kazama, Paul Phoenix, Nina Williams, and Yoshimitsu. Some of them are new to the series, such as Hwoarang, Eddy Gordo, Ling Xiaoyu, and Ogre. Some of them are hidden and can be unlocked by completing certain tasks, such as Dr. Bosconovitch, Gon, Tiger Jackson, and Anna Williams. - A variety of modes and challenges: Tekken 3 offers a variety of modes and challenges that cater to different tastes and preferences. Some of them are: - Arcade: The classic mode where you fight against a series of opponents until you reach the final boss, Ogre. - Versus: The mode where you can fight against another human player or against the computer with your chosen character and settings. - Team Battle: The mode where you can form a team of up to eight characters and fight against another team of up to eight characters. - Time Attack: The mode where you have to beat as many opponents as possible in a limited time. - Survival: The mode where you have to survive as long as possible with a single health bar against an endless stream of opponents. - Tekken Force: The mode where you have to fight your way through four stages of enemies in a side-scrolling beat 'em up style. - Tekken Ball: The mode where you have to hit a beach ball with your attacks and try to knock out your opponent with it. - A fast and fluid gameplay: Tekken 3 has a fast and fluid gameplay that makes it fun and exciting to play. It has a smooth animation, a responsive control, and a balanced system. It also introduces some new features, such as sidestepping, jumping, crouching, and running. It also has a combo system that allows you to chain your attacks together and create your own style. - A stunning graphics and sound effects: Tekken 3 has a stunning graphics and sound effects that make it look and sound amazing. It has a realistic 3D graphics that show the details and expressions of the characters and the environments. It also has a dynamic camera that follows the action from different angles. It also has a great sound effects that match the impact and intensity of the attacks. It also has a catchy soundtrack that fits the mood and atmosphere of the game.Tekken 3 is not an easy game to master. It requires skill, practice, and strategy to beat your opponents. Here are some tips and tricks that can help you improve your game and win more matches:
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-Tekken 3 is not an easy game to master. It requires skill, practice, and strategy to beat your opponents. You need to learn your character's moves, know your opponent's moves, and use the right strategy. You can also use some tips and tricks to improve your game and win more matches.
-Playing Tekken 3 APK for ePSXe on your Android device has many benefits. It allows you to play one of the best fighting games on your Android device anytime and anywhere. It also allows you to relive the nostalgia of playing Tekken 3 on the PlayStation console. It also allows you to challenge yourself and have fun with one of the most entertaining and rewarding games ever.
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-Question | -Answer | -
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Is Tekken 3 APK for ePSXe legal? | -Tekken 3 APK for ePSXe is not legal if you do not own the original Tekken 3 game disc and the PlayStation console. You are only allowed to use the emulator app and the game ISO file if you have the original copies of them. Otherwise, you are violating the copyright laws of Sony and Namco. | -
Is Tekken 3 APK for ePSXe safe? | -Tekken 3 APK for ePSXe is safe if you download it from trusted sources, such as Google Play Store or the official website of ePSXe. You should also scan the files with an antivirus app before installing them on your device. You should also avoid downloading any files from unknown or suspicious sources, as they might contain malware or viruses. | -
Is Tekken 3 APK for ePSXe compatible with all Android devices? | -Tekken 3 APK for ePSXe is compatible with most Android devices that have Android 2.3 or higher versions. However, some devices might have issues with running the emulator app or the game ISO file due to their hardware or software limitations. You should check the compatibility of your device before downloading and installing the files. | -
How can I save my progress in Tekken 3 APK for ePSXe? | -You can save your progress in Tekken 3 APK for ePSXe by using the save state feature of the emulator app. You can access it by tapping on the menu icon on the top right corner of the screen and selecting "Save state". You can choose from five slots to save your state. You can also load your state by selecting "Load state" from the same menu. | -
How can I play multiplayer in Tekken 3 APK for ePSXe? | -You can play multiplayer in Tekken 3 APK for ePSXe by using the split screen feature of the emulator app. You can access it by tapping on the menu icon on the top right corner of the screen and selecting "Split screen". You can choose from two modes: horizontal or vertical split screen. You can also adjust the size of each screen by dragging the divider. You will need two controllers or two touch screens to play multiplayer in split screen mode. | -
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The file you downloaded is a compressed archive that contains the RPCS3 executable file and other data. You will need to extract it before running it.
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Congratulations! You have successfully installed the PS3 firmware on RPCS3. You can now proceed to configure the emulator settings and preferences.
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-The system requirements for RPCS3 are as follows:
-To update RPCS3 to the latest version, follow these steps:
-To save your progress in PS3 games, follow these steps:
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-This is the end of the article. I hope you enjoyed reading it and learned something new. Thank you for your attention and have a nice day!
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- The estimates are close most of the time, but errors can be quite large.
-
- Reducing the random noise (by reducing the number of students who flip heads) increases the accuracy of our estimate, but risks leaking information about students.
-
- If the coin is heavily weighted towards tails, identified students can't credibly claim they reported plagiarizing because they flipped heads.
-
- One surprising way out of this accuracy-privacy tradeoff: carefully collect information from even more people.
-
- If we got students from other schools to fill out this survey, we could accurately measure plagiarism while protecting everyone's privacy. With enough students, we could even start comparing plagiarism across different age groups again—safely this time.
-
- Aggregate statistics about private information are valuable, but can be risky to collect. We want researchers to be able to study things like the connection between demographics and health outcomes without revealing our entire medical history to our neighbors. The coin flipping technique in this article, called randomized response, makes it possible to safely study private information.
-
- You might wonder if coin flipping is the only way to do this. It's not—differential privacy can add targeted bits of random noise to a dataset and guarantee privacy. More flexible than randomized response, the 2020 Census will use it to protect respondents' privacy. In addition to randomizing responses, differential privacy also limits the impact any one response can have on the released data.
-
-
- Adam Pearce and Ellen Jiang // September 2020
-
- Thanks to Carey Radebaugh, Fernanda Viégas, Emily Reif, Hal Abelson, Jess Holbrook, Kristen Olson, Mahima Pushkarna, Martin Wattenberg, Michael Terry, Miguel Guevara, Rebecca Salois, Yannick Assogba, Zan Armstrong and our other colleagues at Google for their help with this piece.
-
-
-
-
- By using this demo you agree to the terms of the Coqui Public Model License at https://coqui.ai/cpml Hanthana Kathawa is a novel by Martin Wickramasinghe, one of the most prominent Sri Lankan writers of the 20th century. The novel was first published in 1947 and has been adapted into a film and a television series. The novel tells the story of Mahinda and Sathya, two university students from different social backgrounds who fall in love despite the obstacles and challenges they face. The novel explores the themes of class, caste, education, culture, and nationalism in post-colonial Sri Lanka. The novel is set in the picturesque Hanthana mountain range near Kandy, where the University of Ceylon was established in 1942. Mahinda is a poor student from a rural village who struggles to fit in with the urban and elite culture of the university. Sathya is a wealthy and beautiful girl from Colombo who is attracted to Mahinda's simplicity and sincerity. Their relationship is opposed by their families, friends, and society, who try to separate them or force them to conform to their expectations. The novel depicts the hardships and sacrifices that Mahinda and Sathya have to endure for their love, as well as their moments of joy and intimacy. DOWNLOAD 🗸 https://urlcod.com/2uIaFX Hanthana Kathawa is considered to be one of the finest examples of Sri Lankan literature, as it portrays the realistic and complex aspects of human emotions and social realities. The novel also reflects the historical and political context of Sri Lanka in the 1940s, when the country was undergoing a transition from British colonial rule to self-government. The novel criticizes the colonial education system that alienated the native students from their own culture and identity, and also questions the role of nationalism and religion in shaping the destiny of the nation. Hanthana Kathawa is a novel that can be enjoyed by readers of all ages and backgrounds, as it offers a universal message of love, courage, and hope. The novel can be downloaded as a PDF file from various online sources[^1^] [^2^], or purchased as a printed book from bookstores. If you are interested in reading more about Hanthana Kathawa and its author, you can visit the Martin Wickramasinghe Trust website, which provides information about his life, works, and legacy. You can also watch the film adaptation of Hanthana Kathawa, which was directed by Sugathapala Senarath Yapa in 1969 and starred Gamini Fonseka and Swarna Mallawarachchi as Mahinda and Sathya. The film is available on YouTube and other online platforms. The television series adaptation of Hanthana Kathawa was aired on Rupavahini in 2008 and featured Nadeeka Gunasekara and Saranga Disasekara as the lead characters. The series can be watched on the Rupavahini website or on other streaming services. Hanthana Kathawa is a novel that has inspired generations of Sri Lankan readers and writers, and has become a part of the national cultural heritage. It is a novel that celebrates the power of love and the beauty of nature, while also exposing the harsh realities of society and politics. It is a novel that will make you laugh, cry, think, and feel. It is a novel that you should not miss. If you are a fan of street soccer and want to experience the thrill of playing with some of the best players in the world, you should definitely try Fifa Street 4. This game is a spin-off of the popular Fifa series, but it focuses on the urban and freestyle aspects of soccer. You can choose from over 50 teams and 35 locations, and customize your own character and style. You can also challenge your friends online or offline in various modes, such as 5-a-side, Futsal, Panna, and Last Man Standing. But how can you get Fifa Street 4 for your PC? Unfortunately, this game was only released for PS3 and Xbox 360 in 2012, and there is no official version for PC. However, there is a way to download Fifa Street 4 PC torrent full version for free, without needing a serial key or a crack. In this article, we will show you how to do it step by step. Download ⏩ https://geags.com/2uCq7P The first thing you need to do is to find a reliable torrent site that has Fifa Street 4 PC torrent available for download. You can use sites like Technosteria, Alitechyt, or pntechcons.com.vn, which have links to download the game with high-speed servers and no viruses. You can also check the comments and ratings of other users to make sure the torrent is working and safe. Once you find a suitable torrent site, you need to download a torrent client, such as uTorrent or BitTorrent, which will allow you to open and download the torrent file. You can download these clients for free from their official websites. After installing the torrent client, you need to click on the download link of Fifa Street 4 PC torrent on the torrent site, and choose to open it with your torrent client. This will start the download process, which may take some time depending on your internet speed and the size of the file. When the download is complete, you will have a folder with all the files of Fifa Street 4 PC game. You need to extract these files using a program like WinRAR or 7-Zip, which are also free to download from their official websites. After extracting the files, you will see an ISO file, which is an image of the game disc. You need to mount this ISO file using a program like Daemon Tools or PowerISO, which will create a virtual drive on your PC that will act as if you inserted the game disc. After mounting the ISO file, you need to run the setup.exe file that will appear on your virtual drive. This will start the installation process of Fifa Street 4 PC game. You need to follow the instructions on the screen and choose the destination folder where you want to install the game. You don't need to enter any serial key or crack during the installation process. When the installation is finished, you can launch Fifa Street 4 PC game from your desktop shortcut or from your start menu. You can also adjust the settings and options of the game according to your preferences. You can now enjoy playing Fifa Street 4 PC game for free! Fifa Street 4 PC game is not just about scoring goals, but also about showing off your skills and style. Here are some tips and tricks that will help you master the game and impress your opponents: Fifa Street 4 PC game is a fun and exciting way to experience street soccer on your computer. By following this guide, you can download Fifa Street 4 PC torrent full version for free and enjoy playing it without any hassle. Have fun! Fifa Street 4 PC game is not only a fun and entertaining game, but also a game that can improve your skills and knowledge of soccer. Here are some of the benefits of playing this game: Although Fifa Street 4 PC game is a well-made and stable game, you may encounter some issues or errors while playing it. Here are some of the common problems and their solutions: Fifa Street 4 is a spin-off of the main Fifa series, but it has some significant differences that make it a unique and enjoyable game. Here are some of the main differences between Fifa Street 4 and other Fifa games: Fifa Street 4 PC game is not only a great game to play solo, but also a great game to play online with friends. You can challenge your friends in various modes, such as 5-a-side, Futsal, Panna, and Last Man Standing. You can also join online tournaments and leagues, and compete with other players from around the world. Here are some steps on how to play Fifa Street 4 PC game online with friends: Fifa Street 4 PC game is a game that has received positive reviews and ratings from critics and players alike. Here are some of the reviews and ratings of Fifa Street 4 PC game from different sources: Some of the common praises for Fifa Street 4 PC game are its fun and addictive gameplay, its realistic and immersive graphics and sound, its diverse and authentic content, and its customizable and creative features. Some of the common criticisms for Fifa Street 4 PC game are its lack of official PC version, its occasional bugs and glitches, its repetitive and limited modes, and its online connectivity issues. If you want to uninstall Fifa Street 4 PC game from your computer, you can follow these simple steps: You can also use a third-party program, such as Revo Uninstaller or IObit Uninstaller, to uninstall Fifa Street 4 PC game more thoroughly and easily. Fifa Street 4 PC game is a game that offers a unique and enjoyable experience of street soccer on your computer. You can download Fifa Street 4 PC torrent full version for free by following this guide, and enjoy playing it without any hassle. You can also learn new tricks and moves, explore different cultures and locations, customize your own character and team, and challenge your friends online or offline in various modes. Fifa Street 4 PC game is a game that will make you love soccer even more. Download ✯✯✯ https://geags.com/2uCq4E If you are a fan of strategy games, you probably have heard of Age of Empires II HD, one of the most popular and acclaimed titles in the genre. This game lets you control one of 18 civilizations from the Middle Ages to the Renaissance, and lead them to victory in various campaigns, scenarios and multiplayer modes. But what if you want to spice up your gameplay and have some fun with cheats? Maybe you want to have unlimited resources, make your units invincible, or create some crazy scenarios with custom units and buildings. Well, that's where Cheat Engine comes in handy. Download Zip ===> https://tinourl.com/2uL11p Age of Empires II HD is a remastered version of the original Age of Empires II: The Age of Kings, released in 2013 by Microsoft Studios. It features improved graphics, sound, compatibility and online features, as well as four official expansions: The Forgotten, The African Kingdoms, Rise of the Rajas and The Last Khans. The game is available on Steam for Windows PC, and has a very active community of players and modders. You can find hundreds of custom maps, scenarios, campaigns and mods on the Steam Workshop or other websites. Cheat Engine is a free and open-source software that allows you to modify single-player games running on Windows. You can use it to scan and change the memory values of any game process, or load cheat tables that contain scripts and pointers for specific games. Cheat Engine can also be used to create trainers, debuggers, speed hacks, disassemblers and more. It is one of the most powerful and versatile tools for cheating in games. Using Cheat Engine for Age of Empires II HD can give you many advantages and possibilities that are not available in the normal game. For example, you can: Using Cheat Engine can also help you overcome some challenges or difficulties in the game. For example, you can: Age of Empire II HD Edition Steam cheat table Using Cheat Engine for Age of Empires II HD is not very hard, but it requires some steps and precautions. Here is a general guide on how to do it: The first thing you need to do is to download and install Cheat Engine on your PC. You can get it from the official website: https://www.cheatengine.org/ Make sure you download the latest version (currently 7.2) and follow the installation instructions. You may need to disable your antivirus or firewall temporarily, as some programs may detect Cheat Engine as a threat. The next thing you need to do is to run both the game and Cheat Engine on your PC. You can launch them in any order, but it is recommended to run Cheat Engine first. You can run the game from Steam or from its executable file (AoK HD.exe). Make sure you run it in windowed mode or borderless windowed mode (you can change this in the game options), as this will make it easier to switch between the game and Cheat Engine. The next thing you need to do is to select the game process in Cheat Engine. To do this: The next thing you need to do is to load a cheat table or scan for values in Cheat Engine. A cheat table is a file that contains scripts and pointers for a specific game that can be loaded into Cheat Engine. A scan for values is a method that allows you to find and change memory values manually by searching for them. To load a cheat table: To scan for values: The last thing you need to do is to activate the cheats you want in Cheat Engine. To do this: There are many cheats you can use with Cheat Engine for Age of Empires II HD, depending on what cheat table you load or what values you scan for. Here are some examples of popular and useful cheats: This cheat allows you to have a minimum amount of resources (food, wood, gold, stone) that will not decrease even if you spend them. You can set the minimum amount to any value you want, for example 16400. To use this cheat, you need to load a cheat table that contains this cheat, such as Recifense's table. Then, you need to activate the cheat by clicking on its box [ ]. You can also change the minimum amount by double-clicking on the value and entering a new one. This cheat is very useful if you want to build a large army or a huge base without worrying about resources. You can also use it to trade resources with your allies or enemies for diplomacy or fun. This cheat makes your units and buildings invincible, meaning they cannot be damaged or killed by any enemy attack. You can also make your units invisible, meaning they cannot be seen or targeted by any enemy unit or building. To use this cheat, you need to load a cheat table that contains this cheat, such as Recifense's table. Then, you need to activate the cheat by clicking on its box [ ]. You can also toggle the invisibility option by double-clicking on it and changing it from 0 to 1 or vice versa. This cheat is very useful if you want to dominate your enemies with ease or explore the map without danger. You can also use it to create some funny situations or scenarios with your units and buildings. This cheat allows you to build, produce and research anything instantly, without any time or cost. You can build any building in one click, produce any unit in one second, and research any technology in one moment. To use this cheat, you need to load a cheat table that contains this cheat, such as Recifense's table. Then, you need to activate the cheat by clicking on its box [ ]. You can also use hotkeys to enable or disable the cheat at any time (Ctrl+PageUp/PageDown for construction/production and Ctrl+Insert/Delete for research). This cheat is very useful if you want to speed up your gameplay or test different strategies or tactics. You can also use it to surprise your enemies with a sudden attack or a technological advantage. This cheat allows you to edit the stats and attributes of any unit or building in the game, as well as the resources and attributes of any player in the game. You can change almost anything about them, such as health, attack, armor, range, speed, position, etc. To use this cheat, you need to load a cheat table that contains this cheat, such as besthsq's table. Then, you need to select a unit or building in the game that you want to edit. The values of that unit or building will appear in the cheat list on the bottom panel. You can change them by double-clicking on them and entering a new value. You can also select a player in the game that you want to edit. The values of that player will appear in the cheat list on the bottom panel. You can change them by double-clicking on them and entering a new value. This cheat is very useful if you want to customize your units and buildings or create some unique scenarios with them. You can also use it to edit your enemies' units and buildings or resources for fun or challenge. In this article, we have learned how to use Cheat Engine for Age of Empires II HD V5.8. We have seen what is Age of Empires II HD and what is Cheat Engine, why use Cheat Engine for Age of Empires II HD, how to use Cheat Engine for Age of Empires II HD, and some examples of cheats you can use with Cheat Engine. We have also learned how to download and install Cheat Engine, how to run the game and Cheat Engine, how to select the game process in Cheat Engine, how to load a cheat table or scan for values in Cheat Engine, and how to activate the cheats you want in Cheat Engine. Before using Cheat Engine for Age of Empires II HD V5.8, please be aware of the following:{u();function c0(t,e){var r=t.type,i=t.value,n,s;return e&&(s=e(t))!==void 0?s:r==="word"||r==="space"?i:r==="string"?(n=t.quote||"",n+i+(t.unclosed?"":n)):r==="comment"?"/*"+i+(t.unclosed?"":"*/"):r==="div"?(t.before||"")+i+(t.after||""):Array.isArray(t.nodes)?(n=p0(t.nodes,e),r!=="function"?n:i+"("+(t.before||"")+n+(t.after||"")+(t.unclosed?"":")")):i}function p0(t,e){var r,i;if(Array.isArray(t)){for(r="",i=t.length-1;~i;i-=1)r=c0(t[i],e)+r;return r}return c0(t,e)}d0.exports=p0});var g0=b((J8,m0)=>{u();var Ys="-".charCodeAt(0),Qs="+".charCodeAt(0),lu=".".charCodeAt(0),WA="e".charCodeAt(0),GA="E".charCodeAt(0);function HA(t){var e=t.charCodeAt(0),r;if(e===Qs||e===Ys){if(r=t.charCodeAt(1),r>=48&&r<=57)return!0;var i=t.charCodeAt(2);return r===lu&&i>=48&&i<=57}return e===lu?(r=t.charCodeAt(1),r>=48&&r<=57):e>=48&&e<=57}m0.exports=function(t){var e=0,r=t.length,i,n,s;if(r===0||!HA(t))return!1;for(i=t.charCodeAt(e),(i===Qs||i===Ys)&&e++;e
", unsafe_allow_html=True)
-
-"""
-# Training Code Generator for Hugging Face Models 🤗
-"""
-st.markdown("
", unsafe_allow_html=True)
-"""
----
-"""
-
-inputs = {}
-
-with st.sidebar:
- st.info(
- "**Select the configuration**"
- )
- inputs = show_API_component(inputs)
- inputs = show_task_component(inputs)
- inputs = show_model_component(inputs)
- inputs = show_input_data_component(inputs)
- inputs = show_preprocessing_component(inputs)
- inputs = show_training_comoponent(inputs)
-
-inputs = show_datset_view_component(inputs)
-inputs = show_code_component(inputs)
\ No newline at end of file
diff --git a/spaces/krishw/MovieExplorer/conf.py b/spaces/krishw/MovieExplorer/conf.py
deleted file mode 100644
index 9db8caad2c083e04f8eed9bdcae1df85dda2b83b..0000000000000000000000000000000000000000
--- a/spaces/krishw/MovieExplorer/conf.py
+++ /dev/null
@@ -1,3 +0,0 @@
-# Used .gitignore to hide api key
-
-api_key = 'fdb378a1a8e6a38bc30049ee94f2b87a'
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/filelock/_error.py b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/filelock/_error.py
deleted file mode 100644
index e2bd65305443e12fc61e16c894e8ab82a50c8ec2..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/filelock/_error.py
+++ /dev/null
@@ -1,30 +0,0 @@
-from __future__ import annotations
-
-from typing import Any
-
-
-class Timeout(TimeoutError):
- """Raised when the lock could not be acquired in *timeout* seconds."""
-
- def __init__(self, lock_file: str) -> None:
- super().__init__()
- self._lock_file = lock_file
-
- def __reduce__(self) -> str | tuple[Any, ...]:
- return self.__class__, (self._lock_file,) # Properly pickle the exception
-
- def __str__(self) -> str:
- return f"The file lock '{self._lock_file}' could not be acquired."
-
- def __repr__(self) -> str:
- return f"{self.__class__.__name__}({self.lock_file!r})"
-
- @property
- def lock_file(self) -> str:
- """:return: The path of the file lock."""
- return self._lock_file
-
-
-__all__ = [
- "Timeout",
-]
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/deploy_space.py b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/deploy_space.py
deleted file mode 100644
index 9014b4e24ea2987d05dcf6ad58a6f0ee437646de..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/deploy_space.py
+++ /dev/null
@@ -1,175 +0,0 @@
-from __future__ import annotations
-
-import argparse
-import os
-import re
-
-import huggingface_hub
-
-import gradio as gr
-
-repo_directory = os.getcwd()
-readme_file = os.path.join(repo_directory, "README.md")
-github_action_template = os.path.join(
- os.path.dirname(__file__), "deploy_space_action.yaml"
-)
-
-
-def add_configuration_to_readme(
- title: str | None,
- app_file: str | None,
-) -> dict:
- configuration = {}
-
- dir_name = os.path.basename(repo_directory)
- if title is None:
- title = input(f"Enter Spaces app title [{dir_name}]: ") or dir_name
- formatted_title = format_title(title)
- if formatted_title != title:
- print(f"Formatted to {formatted_title}. ")
- configuration["title"] = formatted_title
-
- if app_file is None:
- for file in os.listdir(repo_directory):
- file_path = os.path.join(repo_directory, file)
- if not os.path.isfile(file_path) or not file.endswith(".py"):
- continue
-
- with open(file_path, encoding="utf-8", errors="ignore") as f:
- content = f.read()
- if "import gradio" in content:
- app_file = file
- break
-
- app_file = (
- input(f"Enter Gradio app file {f'[{app_file}]' if app_file else ''}: ")
- or app_file
- )
- if not app_file or not os.path.exists(app_file):
- raise FileNotFoundError("Failed to find Gradio app file.")
- configuration["app_file"] = app_file
-
- configuration["sdk"] = "gradio"
- configuration["sdk_version"] = gr.__version__
- huggingface_hub.metadata_save(readme_file, configuration)
-
- configuration["hardware"] = (
- input(
- f"Enter Spaces hardware ({', '.join(hardware.value for hardware in huggingface_hub.SpaceHardware)}) [cpu-basic]: "
- )
- or "cpu-basic"
- )
-
- secrets = {}
- if input("Any Spaces secrets (y/n) [n]: ") == "y":
- while True:
- secret_name = input("Enter secret name (leave blank to end): ")
- if not secret_name:
- break
- secret_value = input(f"Enter secret value for {secret_name}: ")
- secrets[secret_name] = secret_value
- configuration["secrets"] = secrets
-
- requirements_file = os.path.join(repo_directory, "requirements.txt")
- if (
- not os.path.exists(requirements_file)
- and input("Create requirements.txt file? (y/n) [n]: ").lower() == "y"
- ):
- while True:
- requirement = input("Enter a dependency (leave blank to end): ")
- if not requirement:
- break
- with open(requirements_file, "a") as f:
- f.write(requirement + "\n")
-
- if (
- input(
- "Create Github Action to automatically update Space on 'git push'? [n]: "
- ).lower()
- == "y"
- ):
- track_branch = input("Enter branch to track [main]: ") or "main"
- github_action_file = os.path.join(
- repo_directory, ".github/workflows/update_space.yml"
- )
- os.makedirs(os.path.dirname(github_action_file), exist_ok=True)
- with open(github_action_template) as f:
- github_action_content = f.read()
- github_action_content = github_action_content.replace("$branch", track_branch)
- with open(github_action_file, "w") as f:
- f.write(github_action_content)
-
- print(
- "Github Action created. Add your Hugging Face write token (from https://huggingface.co/settings/tokens) as an Actions Secret named 'hf_token' to your GitHub repository. This can be set in your repository's settings page."
- )
-
- return configuration
-
-
-def format_title(title: str):
- title = title.replace(" ", "_")
- title = re.sub(r"[^a-zA-Z0-9\-._]", "", title)
- title = re.sub("-+", "-", title)
- while title.startswith("."):
- title = title[1:]
- return title
-
-
-def deploy():
- if (
- os.getenv("SYSTEM") == "spaces"
- ): # in case a repo with this function is uploaded to spaces
- return
- parser = argparse.ArgumentParser(description="Deploy to Spaces")
- parser.add_argument("deploy")
- parser.add_argument("--title", type=str, help="Spaces app title")
- parser.add_argument("--app-file", type=str, help="File containing the Gradio app")
-
- args = parser.parse_args()
-
- hf_api = huggingface_hub.HfApi()
- whoami = None
- login = False
- try:
- whoami = hf_api.whoami()
- if whoami["auth"]["accessToken"]["role"] != "write":
- login = True
- except OSError:
- login = True
- if login:
- print("Need 'write' access token to create a Spaces repo.")
- huggingface_hub.login(add_to_git_credential=False)
- whoami = hf_api.whoami()
-
- configuration: None | dict = None
- if os.path.exists(readme_file):
- try:
- configuration = huggingface_hub.metadata_load(readme_file)
- except ValueError:
- pass
-
- if configuration is None:
- print(
- f"Creating new Spaces Repo in '{repo_directory}'. Collecting metadata, press Enter to accept default value."
- )
- configuration = add_configuration_to_readme(
- args.title,
- args.app_file,
- )
-
- space_id = huggingface_hub.create_repo(
- configuration["title"],
- space_sdk="gradio",
- repo_type="space",
- exist_ok=True,
- space_hardware=configuration.get("hardware"),
- ).repo_id
- hf_api.upload_folder(
- repo_id=space_id,
- repo_type="space",
- folder_path=repo_directory,
- )
- if configuration.get("secrets"):
- for secret_name, secret_value in configuration["secrets"].items():
- huggingface_hub.add_space_secret(space_id, secret_name, secret_value)
- print(f"Space available at https://huggingface.co/spaces/{space_id}")
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/jinja2/idtracking.py b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/jinja2/idtracking.py
deleted file mode 100644
index 995ebaa0c8178ddb9e0479e0e9f6d30ed863a785..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/jinja2/idtracking.py
+++ /dev/null
@@ -1,318 +0,0 @@
-import typing as t
-
-from . import nodes
-from .visitor import NodeVisitor
-
-VAR_LOAD_PARAMETER = "param"
-VAR_LOAD_RESOLVE = "resolve"
-VAR_LOAD_ALIAS = "alias"
-VAR_LOAD_UNDEFINED = "undefined"
-
-
-def find_symbols(
- nodes: t.Iterable[nodes.Node], parent_symbols: t.Optional["Symbols"] = None
-) -> "Symbols":
- sym = Symbols(parent=parent_symbols)
- visitor = FrameSymbolVisitor(sym)
- for node in nodes:
- visitor.visit(node)
- return sym
-
-
-def symbols_for_node(
- node: nodes.Node, parent_symbols: t.Optional["Symbols"] = None
-) -> "Symbols":
- sym = Symbols(parent=parent_symbols)
- sym.analyze_node(node)
- return sym
-
-
-class Symbols:
- def __init__(
- self, parent: t.Optional["Symbols"] = None, level: t.Optional[int] = None
- ) -> None:
- if level is None:
- if parent is None:
- level = 0
- else:
- level = parent.level + 1
-
- self.level: int = level
- self.parent = parent
- self.refs: t.Dict[str, str] = {}
- self.loads: t.Dict[str, t.Any] = {}
- self.stores: t.Set[str] = set()
-
- def analyze_node(self, node: nodes.Node, **kwargs: t.Any) -> None:
- visitor = RootVisitor(self)
- visitor.visit(node, **kwargs)
-
- def _define_ref(
- self, name: str, load: t.Optional[t.Tuple[str, t.Optional[str]]] = None
- ) -> str:
- ident = f"l_{self.level}_{name}"
- self.refs[name] = ident
- if load is not None:
- self.loads[ident] = load
- return ident
-
- def find_load(self, target: str) -> t.Optional[t.Any]:
- if target in self.loads:
- return self.loads[target]
-
- if self.parent is not None:
- return self.parent.find_load(target)
-
- return None
-
- def find_ref(self, name: str) -> t.Optional[str]:
- if name in self.refs:
- return self.refs[name]
-
- if self.parent is not None:
- return self.parent.find_ref(name)
-
- return None
-
- def ref(self, name: str) -> str:
- rv = self.find_ref(name)
- if rv is None:
- raise AssertionError(
- "Tried to resolve a name to a reference that was"
- f" unknown to the frame ({name!r})"
- )
- return rv
-
- def copy(self) -> "Symbols":
- rv = object.__new__(self.__class__)
- rv.__dict__.update(self.__dict__)
- rv.refs = self.refs.copy()
- rv.loads = self.loads.copy()
- rv.stores = self.stores.copy()
- return rv
-
- def store(self, name: str) -> None:
- self.stores.add(name)
-
- # If we have not see the name referenced yet, we need to figure
- # out what to set it to.
- if name not in self.refs:
- # If there is a parent scope we check if the name has a
- # reference there. If it does it means we might have to alias
- # to a variable there.
- if self.parent is not None:
- outer_ref = self.parent.find_ref(name)
- if outer_ref is not None:
- self._define_ref(name, load=(VAR_LOAD_ALIAS, outer_ref))
- return
-
- # Otherwise we can just set it to undefined.
- self._define_ref(name, load=(VAR_LOAD_UNDEFINED, None))
-
- def declare_parameter(self, name: str) -> str:
- self.stores.add(name)
- return self._define_ref(name, load=(VAR_LOAD_PARAMETER, None))
-
- def load(self, name: str) -> None:
- if self.find_ref(name) is None:
- self._define_ref(name, load=(VAR_LOAD_RESOLVE, name))
-
- def branch_update(self, branch_symbols: t.Sequence["Symbols"]) -> None:
- stores: t.Dict[str, int] = {}
- for branch in branch_symbols:
- for target in branch.stores:
- if target in self.stores:
- continue
- stores[target] = stores.get(target, 0) + 1
-
- for sym in branch_symbols:
- self.refs.update(sym.refs)
- self.loads.update(sym.loads)
- self.stores.update(sym.stores)
-
- for name, branch_count in stores.items():
- if branch_count == len(branch_symbols):
- continue
-
- target = self.find_ref(name) # type: ignore
- assert target is not None, "should not happen"
-
- if self.parent is not None:
- outer_target = self.parent.find_ref(name)
- if outer_target is not None:
- self.loads[target] = (VAR_LOAD_ALIAS, outer_target)
- continue
- self.loads[target] = (VAR_LOAD_RESOLVE, name)
-
- def dump_stores(self) -> t.Dict[str, str]:
- rv: t.Dict[str, str] = {}
- node: t.Optional["Symbols"] = self
-
- while node is not None:
- for name in sorted(node.stores):
- if name not in rv:
- rv[name] = self.find_ref(name) # type: ignore
-
- node = node.parent
-
- return rv
-
- def dump_param_targets(self) -> t.Set[str]:
- rv = set()
- node: t.Optional["Symbols"] = self
-
- while node is not None:
- for target, (instr, _) in self.loads.items():
- if instr == VAR_LOAD_PARAMETER:
- rv.add(target)
-
- node = node.parent
-
- return rv
-
-
-class RootVisitor(NodeVisitor):
- def __init__(self, symbols: "Symbols") -> None:
- self.sym_visitor = FrameSymbolVisitor(symbols)
-
- def _simple_visit(self, node: nodes.Node, **kwargs: t.Any) -> None:
- for child in node.iter_child_nodes():
- self.sym_visitor.visit(child)
-
- visit_Template = _simple_visit
- visit_Block = _simple_visit
- visit_Macro = _simple_visit
- visit_FilterBlock = _simple_visit
- visit_Scope = _simple_visit
- visit_If = _simple_visit
- visit_ScopedEvalContextModifier = _simple_visit
-
- def visit_AssignBlock(self, node: nodes.AssignBlock, **kwargs: t.Any) -> None:
- for child in node.body:
- self.sym_visitor.visit(child)
-
- def visit_CallBlock(self, node: nodes.CallBlock, **kwargs: t.Any) -> None:
- for child in node.iter_child_nodes(exclude=("call",)):
- self.sym_visitor.visit(child)
-
- def visit_OverlayScope(self, node: nodes.OverlayScope, **kwargs: t.Any) -> None:
- for child in node.body:
- self.sym_visitor.visit(child)
-
- def visit_For(
- self, node: nodes.For, for_branch: str = "body", **kwargs: t.Any
- ) -> None:
- if for_branch == "body":
- self.sym_visitor.visit(node.target, store_as_param=True)
- branch = node.body
- elif for_branch == "else":
- branch = node.else_
- elif for_branch == "test":
- self.sym_visitor.visit(node.target, store_as_param=True)
- if node.test is not None:
- self.sym_visitor.visit(node.test)
- return
- else:
- raise RuntimeError("Unknown for branch")
-
- if branch:
- for item in branch:
- self.sym_visitor.visit(item)
-
- def visit_With(self, node: nodes.With, **kwargs: t.Any) -> None:
- for target in node.targets:
- self.sym_visitor.visit(target)
- for child in node.body:
- self.sym_visitor.visit(child)
-
- def generic_visit(self, node: nodes.Node, *args: t.Any, **kwargs: t.Any) -> None:
- raise NotImplementedError(f"Cannot find symbols for {type(node).__name__!r}")
-
-
-class FrameSymbolVisitor(NodeVisitor):
- """A visitor for `Frame.inspect`."""
-
- def __init__(self, symbols: "Symbols") -> None:
- self.symbols = symbols
-
- def visit_Name(
- self, node: nodes.Name, store_as_param: bool = False, **kwargs: t.Any
- ) -> None:
- """All assignments to names go through this function."""
- if store_as_param or node.ctx == "param":
- self.symbols.declare_parameter(node.name)
- elif node.ctx == "store":
- self.symbols.store(node.name)
- elif node.ctx == "load":
- self.symbols.load(node.name)
-
- def visit_NSRef(self, node: nodes.NSRef, **kwargs: t.Any) -> None:
- self.symbols.load(node.name)
-
- def visit_If(self, node: nodes.If, **kwargs: t.Any) -> None:
- self.visit(node.test, **kwargs)
- original_symbols = self.symbols
-
- def inner_visit(nodes: t.Iterable[nodes.Node]) -> "Symbols":
- self.symbols = rv = original_symbols.copy()
-
- for subnode in nodes:
- self.visit(subnode, **kwargs)
-
- self.symbols = original_symbols
- return rv
-
- body_symbols = inner_visit(node.body)
- elif_symbols = inner_visit(node.elif_)
- else_symbols = inner_visit(node.else_ or ())
- self.symbols.branch_update([body_symbols, elif_symbols, else_symbols])
-
- def visit_Macro(self, node: nodes.Macro, **kwargs: t.Any) -> None:
- self.symbols.store(node.name)
-
- def visit_Import(self, node: nodes.Import, **kwargs: t.Any) -> None:
- self.generic_visit(node, **kwargs)
- self.symbols.store(node.target)
-
- def visit_FromImport(self, node: nodes.FromImport, **kwargs: t.Any) -> None:
- self.generic_visit(node, **kwargs)
-
- for name in node.names:
- if isinstance(name, tuple):
- self.symbols.store(name[1])
- else:
- self.symbols.store(name)
-
- def visit_Assign(self, node: nodes.Assign, **kwargs: t.Any) -> None:
- """Visit assignments in the correct order."""
- self.visit(node.node, **kwargs)
- self.visit(node.target, **kwargs)
-
- def visit_For(self, node: nodes.For, **kwargs: t.Any) -> None:
- """Visiting stops at for blocks. However the block sequence
- is visited as part of the outer scope.
- """
- self.visit(node.iter, **kwargs)
-
- def visit_CallBlock(self, node: nodes.CallBlock, **kwargs: t.Any) -> None:
- self.visit(node.call, **kwargs)
-
- def visit_FilterBlock(self, node: nodes.FilterBlock, **kwargs: t.Any) -> None:
- self.visit(node.filter, **kwargs)
-
- def visit_With(self, node: nodes.With, **kwargs: t.Any) -> None:
- for target in node.values:
- self.visit(target)
-
- def visit_AssignBlock(self, node: nodes.AssignBlock, **kwargs: t.Any) -> None:
- """Stop visiting at block assigns."""
- self.visit(node.target, **kwargs)
-
- def visit_Scope(self, node: nodes.Scope, **kwargs: t.Any) -> None:
- """Stop visiting at scopes."""
-
- def visit_Block(self, node: nodes.Block, **kwargs: t.Any) -> None:
- """Stop visiting at blocks."""
-
- def visit_OverlayScope(self, node: nodes.OverlayScope, **kwargs: t.Any) -> None:
- """Do not visit into overlay scopes."""
diff --git a/spaces/leafShen/CodeFormer/CodeFormer/facelib/detection/yolov5face/models/experimental.py b/spaces/leafShen/CodeFormer/CodeFormer/facelib/detection/yolov5face/models/experimental.py
deleted file mode 100644
index 37ba4c4420789c92dc0e2aaeb3d5b64859ec728c..0000000000000000000000000000000000000000
--- a/spaces/leafShen/CodeFormer/CodeFormer/facelib/detection/yolov5face/models/experimental.py
+++ /dev/null
@@ -1,45 +0,0 @@
-# # This file contains experimental modules
-
-import numpy as np
-import torch
-from torch import nn
-
-from facelib.detection.yolov5face.models.common import Conv
-
-
-class CrossConv(nn.Module):
- # Cross Convolution Downsample
- def __init__(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False):
- # ch_in, ch_out, kernel, stride, groups, expansion, shortcut
- super().__init__()
- c_ = int(c2 * e) # hidden channels
- self.cv1 = Conv(c1, c_, (1, k), (1, s))
- self.cv2 = Conv(c_, c2, (k, 1), (s, 1), g=g)
- self.add = shortcut and c1 == c2
-
- def forward(self, x):
- return x + self.cv2(self.cv1(x)) if self.add else self.cv2(self.cv1(x))
-
-
-class MixConv2d(nn.Module):
- # Mixed Depthwise Conv https://arxiv.org/abs/1907.09595
- def __init__(self, c1, c2, k=(1, 3), s=1, equal_ch=True):
- super().__init__()
- groups = len(k)
- if equal_ch: # equal c_ per group
- i = torch.linspace(0, groups - 1e-6, c2).floor() # c2 indices
- c_ = [(i == g).sum() for g in range(groups)] # intermediate channels
- else: # equal weight.numel() per group
- b = [c2] + [0] * groups
- a = np.eye(groups + 1, groups, k=-1)
- a -= np.roll(a, 1, axis=1)
- a *= np.array(k) ** 2
- a[0] = 1
- c_ = np.linalg.lstsq(a, b, rcond=None)[0].round() # solve for equal weight indices, ax = b
-
- self.m = nn.ModuleList([nn.Conv2d(c1, int(c_[g]), k[g], s, k[g] // 2, bias=False) for g in range(groups)])
- self.bn = nn.BatchNorm2d(c2)
- self.act = nn.LeakyReLU(0.1, inplace=True)
-
- def forward(self, x):
- return x + self.act(self.bn(torch.cat([m(x) for m in self.m], 1)))
diff --git a/spaces/leurez/moss/src/views/chat/hooks/useCopyCode.ts b/spaces/leurez/moss/src/views/chat/hooks/useCopyCode.ts
deleted file mode 100644
index 8816b5dd385b36797c636fbebc081b72893698a5..0000000000000000000000000000000000000000
--- a/spaces/leurez/moss/src/views/chat/hooks/useCopyCode.ts
+++ /dev/null
@@ -1,24 +0,0 @@
-import { onMounted, onUpdated } from 'vue'
-import { copyText } from '@/utils/format'
-
-export function useCopyCode() {
- function copyCodeBlock() {
- const codeBlockWrapper = document.querySelectorAll('.code-block-wrapper')
- codeBlockWrapper.forEach((wrapper) => {
- const copyBtn = wrapper.querySelector('.code-block-header__copy')
- const codeBlock = wrapper.querySelector('.code-block-body')
- if (copyBtn && codeBlock) {
- copyBtn.addEventListener('click', () => {
- if (navigator.clipboard?.writeText)
- navigator.clipboard.writeText(codeBlock.textContent ?? '')
- else
- copyText({ text: codeBlock.textContent ?? '', origin: true })
- })
- }
- })
- }
-
- onMounted(() => copyCodeBlock())
-
- onUpdated(() => copyCodeBlock())
-}
diff --git a/spaces/lewiswu1209/MockingBird/vocoder_train.py b/spaces/lewiswu1209/MockingBird/vocoder_train.py
deleted file mode 100644
index f618ee00d8f774ecf821b9714932acc7e99aa5d5..0000000000000000000000000000000000000000
--- a/spaces/lewiswu1209/MockingBird/vocoder_train.py
+++ /dev/null
@@ -1,92 +0,0 @@
-from utils.argutils import print_args
-from vocoder.wavernn.train import train
-from vocoder.hifigan.train import train as train_hifigan
-from vocoder.fregan.train import train as train_fregan
-from utils.util import AttrDict
-from pathlib import Path
-import argparse
-import json
-import torch
-import torch.multiprocessing as mp
-
-if __name__ == "__main__":
- parser = argparse.ArgumentParser(
- description="Trains the vocoder from the synthesizer audios and the GTA synthesized mels, "
- "or ground truth mels.",
- formatter_class=argparse.ArgumentDefaultsHelpFormatter
- )
-
- parser.add_argument("run_id", type=str, help= \
- "Name for this model instance. If a model state from the same run ID was previously "
- "saved, the training will restart from there. Pass -f to overwrite saved states and "
- "restart from scratch.")
- parser.add_argument("datasets_root", type=str, help= \
- "Path to the directory containing your SV2TTS directory. Specifying --syn_dir or --voc_dir "
- "will take priority over this argument.")
- parser.add_argument("vocoder_type", type=str, default="wavernn", help= \
- "Choose the vocoder type for train. Defaults to wavernn"
- "Now, Support AutoCAD 2007 full version
-
- d5da3c52bf
-
-
-
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/ESET Internet Security 12.2.29.0 Crack With Serial Key Free Download 2019 Extra Quality.md b/spaces/lincquiQcaudo/Top-20-Diffusion/ESET Internet Security 12.2.29.0 Crack With Serial Key Free Download 2019 Extra Quality.md
deleted file mode 100644
index 88282daa3fc90d17e3f7efa80df4ee68c0cd80ec..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/ESET Internet Security 12.2.29.0 Crack With Serial Key Free Download 2019 Extra Quality.md
+++ /dev/null
@@ -1,27 +0,0 @@
-
-ESET Internet Security 12.2.29.0 Crack With Serial Key Free Download 2019
-ESET Internet Security 12.2.29.0 Crack With Serial Key Free Download 2019
-
-
-
-
-
\ No newline at end of file
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/HOT! XforcekeygenRobotStructuralAnalysisProfessional2015FreeDownload.md b/spaces/lincquiQcaudo/Top-20-Diffusion/HOT! XforcekeygenRobotStructuralAnalysisProfessional2015FreeDownload.md
deleted file mode 100644
index 6503b427a98996817eea5f3cd27e0c74e99dc334..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/HOT! XforcekeygenRobotStructuralAnalysisProfessional2015FreeDownload.md
+++ /dev/null
@@ -1,6 +0,0 @@
-xforcekeygenRobotStructuralAnalysisProfessional2015FreeDownload
-
-Computer-Aided Thermodynamic Tables · microwind 3.5 full version 65 · xforcekeygenRobotStructuralAnalysisProfessional2015FreeDownload 4d29de3e1b
-
-
-
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/Libro Trabajo Y Ciudadania Editorial Maipue Pdf __LINK__ Download.md b/spaces/lincquiQcaudo/Top-20-Diffusion/Libro Trabajo Y Ciudadania Editorial Maipue Pdf __LINK__ Download.md
deleted file mode 100644
index 0c0c25e3a7b26efe0d68e7dc219ee3a6544b2bd6..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/Libro Trabajo Y Ciudadania Editorial Maipue Pdf __LINK__ Download.md
+++ /dev/null
@@ -1,8 +0,0 @@
-Libro Trabajo Y Ciudadania Editorial Maipue Pdf Download
-
-... /3006915-book-work-and-citizenship-editorial-maipue-pdf-371-brankame h-washington-congress/;
-
-... /3006964-book-work-and-citizenship-editorial-maipue-manual-distribution-in-branch-volume-edition-standard-citizenship-editorial-maipue-manual-distribution-in-branch-volume-edition-standard-citizenship-editorial-maipu-manual-distribution-in-branch-volume-edition-standard-citizenship-editorial-maipue-manual-distribution-in-branch-volume-edition-st 8a78ff9644
-
-
-
diff --git a/spaces/littlegoldfish/simple_chatbot/app.py b/spaces/littlegoldfish/simple_chatbot/app.py
deleted file mode 100644
index 9326e6ee34f3b049e03c90eb75885f1fe2b9fdf4..0000000000000000000000000000000000000000
--- a/spaces/littlegoldfish/simple_chatbot/app.py
+++ /dev/null
@@ -1,57 +0,0 @@
-import openai
-import os
-
-openai.api_key = os.environ.get("OPENAI_API_KEY")
-
-class Conversation:
- def __init__(self, prompt, num_of_round):
- self.prompt = prompt
- self.num_of_round = num_of_round
- self.messages = []
- self.messages.append({"role": "system", "content": self.prompt})
-
- def ask(self, question):
- try:
- self.messages.append({"role": "user", "content": question})
- response = openai.ChatCompletion.create(
- model="gpt-3.5-turbo",
- messages=self.messages,
- temperature=0.5,
- max_tokens=2048,
- top_p=1,
- )
- except Exception as e:
- print(e)
- return e
-
- message = response["choices"][0]["message"]["content"]
- self.messages.append({"role": "assistant", "content": message})
-
- if len(self.messages) > self.num_of_round*2 + 1:
- del self.messages[1:3] #Remove the first round conversation left.
- return message
-
-import gradio as gr
-prompt = """你是一个中国厨师,用中文回答做菜的问题。你的回答需要满足以下要求:
-1. 你的回答必须是中文
-2. 回答限制在100个字以内"""
-
-conv = Conversation(prompt, 10)
-
-def answer(question, history=[]):
- history.append(question)
- response = conv.ask(question)
- history.append(response)
- responses = [(u,b) for u,b in zip(history[::2], history[1::2])]
- return responses, history
-
-with gr.Blocks(css="#chatbot{height:300px} .overflow-y-auto{height:500px}") as demo:
- chatbot = gr.Chatbot(elem_id="chatbot")
- state = gr.State([])
-
- with gr.Row():
- txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
-
- txt.submit(answer, [txt, state], [chatbot, state])
-
-demo.launch()
\ No newline at end of file
diff --git a/spaces/locust/03-NLP-MLM-MaskedLanguageModel/README.md b/spaces/locust/03-NLP-MLM-MaskedLanguageModel/README.md
deleted file mode 100644
index b1e3c62203b9f349e844a4f18d1575f73116cff1..0000000000000000000000000000000000000000
--- a/spaces/locust/03-NLP-MLM-MaskedLanguageModel/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: 03 NLP MLM MaskedLanguageModel
-emoji: 🐠
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.1.7
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/ltgoslo/ssa-perin/data/field/anchored_label_field.py b/spaces/ltgoslo/ssa-perin/data/field/anchored_label_field.py
deleted file mode 100644
index 33a8c65ddfaaaf37f1c377842a9f99cd1b2ca529..0000000000000000000000000000000000000000
--- a/spaces/ltgoslo/ssa-perin/data/field/anchored_label_field.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import torch
-from data.field.mini_torchtext.field import RawField
-
-
-class AnchoredLabelField(RawField):
- def __init__(self):
- super(AnchoredLabelField, self).__init__()
- self.vocab = None
-
- def process(self, example, device=None):
- example = self.numericalize(example)
- tensor = self.pad(example, device)
- return tensor
-
- def pad(self, example, device):
- n_labels = len(self.vocab)
- n_nodes, n_tokens = len(example[1]), example[0]
-
- tensor = torch.full([n_nodes, n_tokens, n_labels + 1], 0, dtype=torch.long, device=device)
- for i_node, node in enumerate(example[1]):
- for anchor, rule in node:
- tensor[i_node, anchor, rule + 1] = 1
-
- return tensor
-
- def numericalize(self, arr):
- def multi_map(array, function):
- if isinstance(array, tuple):
- return (array[0], function(array[1]))
- elif isinstance(array, list):
- return [multi_map(a, function) for a in array]
- else:
- return array
-
- if self.vocab is not None:
- arr = multi_map(arr, lambda x: self.vocab.stoi[x] if x in self.vocab.stoi else 0)
-
- return arr
diff --git a/spaces/lunarring/latentblending/ldm/modules/midas/__init__.py b/spaces/lunarring/latentblending/ldm/modules/midas/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/ma-xu/LIVE/thrust/thrust/detail/functional/placeholder.h b/spaces/ma-xu/LIVE/thrust/thrust/detail/functional/placeholder.h
deleted file mode 100644
index d0832cfecb1c70dd28d78c44349f0ee5ad78c0fa..0000000000000000000000000000000000000000
--- a/spaces/ma-xu/LIVE/thrust/thrust/detail/functional/placeholder.h
+++ /dev/null
@@ -1,39 +0,0 @@
-/*
- * Copyright 2008-2013 NVIDIA Corporation
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#pragma once
-
-#include
-
- Explorables
-
How randomized response can help collect sensitive information responsibly
- Anonymous Data
-
-Revealed Information
-Randomization
-How far off can we be?
-
-Conclusion
-
-Credits
-
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-
-
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-
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-
-
-
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-
-
-
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-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
\ No newline at end of file
diff --git a/spaces/merve/data-leak/public/fill-in-the-blank/README.md b/spaces/merve/data-leak/public/fill-in-the-blank/README.md
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/merve/dataset-worldviews/public/anonymization/make-gs.js b/spaces/merve/dataset-worldviews/public/anonymization/make-gs.js
deleted file mode 100644
index 4eb1aaeffeb2a69e726a9d452d7eea7b3352b318..0000000000000000000000000000000000000000
--- a/spaces/merve/dataset-worldviews/public/anonymization/make-gs.js
+++ /dev/null
@@ -1,105 +0,0 @@
-window.makeGS = function(){
- var prevSlideIndex = -1
- function updateSlide(i){
- var slide = slides[i]
- if (!slide) return
-
- d3.select('.tooltip').classed('tooltip-hidden', true)
-
- var dur = 500
-
- sel.student.transition('xKey').duration(dur).delay(dur ? slide.circleDelayFn : 0)
- .translate(d => (d.isAdditionalStudent && slide.xKey != 'plagerizedShifted') ? [0,0]: d.pos[slide.xKey])
-
-
- if (sel.rectAt[slide.xKey]){
- sel.uniqueBox.transition('at').duration(dur)
- .delay(d => dur ? slide.circleDelayFn(d.d0) : 0)
- .at(sel.rectAt[slide.xKey])
- .translate(d => d.d0.group[slide.xKey].pos)
- }
-
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- .st({opacity: slide.showUniqueBox ? 1 : 0})
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- sel.uniqueSeasonBox.transition()
- .delay((d, i) => slide.showUniqueSeasonBox ? dur*2 + i*40 : 0).duration(slide.showUniqueSeasonBox ? 0 : dur)
- .st({opacity: slide.showUniqueSeasonBox ? 1 : 0})
-
-
- if (sliders.headsProb != slide.headsProbTarget && slide.animateHeadsProbSlider != -1){
- var headI = d3.interpolate(sliders.headsProb, slide.headsProbTarget)
- if (window.headSliderTimer) window.headSliderTimer.stop()
- window.headSliderTimer = d3.timer(ms => {
- var dur = slide.animateHeadsProbSlider ? 2000 : 1
- var t = d3.easeCubicInOut(d3.clamp(0, ms/dur, 1))
- sliders.updateHeadsProb(headI(t))
- if (t == 1) headSliderTimer.stop()
- })
- }
-
- if (sliders.population != slide.populationTarget){
- var popI = d3.interpolate(sliders.population, slide.populationTarget)
- if (window.popSliderTimer) window.popSliderTimer.stop()
- window.popSliderTimer = d3.timer(ms => {
- var dur = slide.animatePopulationSlider ? 2000 : 1
- var t = d3.easeCubicInOut(d3.clamp(0, ms/dur, 1))
- sliders.updatePopulation(Math.round(popI(t)/2)*2)
- if (t == 1) popSliderTimer.stop()
- })
- }
-
- axii.stateAxis.transition().duration(dur/2)
- .st({opacity: slide.showStateAxis ? 1 : 0})
- axii.ageAxis.transition().duration(dur/2)
- .st({opacity: slide.showAgeAxis ? 1 : 0})
- axii.seasonAxis.transition().duration(dur/2)
- .st({opacity: slide.showSeasonAxis ? 1 : 0})
- axii.headAxis.transition().duration(dur/2)
- .st({opacity: slide.showHeadAxis ? 1 : 0})
- axii.headCaptionAxis.transition().duration(dur/2)
- .st({opacity: slide.showHeadCaptionAxis ? 1 : 0})
- estimates.axisSel.transition().delay(dur).duration(dur/2)
- .st({opacity: slide.showHistogramAxis ? 1 : 0})
- estimates.activeSel.transition().delay(dur).duration(dur/2)
- .st({opacity: slide.showHistogramAxis ? 1 : 0})
- // axii.estimateAxis.transition().delay(dur).duration(dur/2)
- // .st({opacity: slide.showEstimate && !slide.enterHistogram ? 1 : 0})
- // axii.plagerizedAxis.transition().delay(dur).duration(dur/2)
- // .st({opacity: slide.showPlagerizedAxis ? 1 : 0})
-
-
- annotationSel.transition().duration(dur/2)
- .st({opacity: d => i == d.slide ? 1 : 0})
-
- estimates.containerSel.transition('xKey').duration(dur/2)
- .st({opacity: slide.showHistogram ? 1 : 0})
-
- if (slide.enterHistogram){
- estimates.render(true)
- } else {
- window.flipAllCoinsTimer._time = Infinity
- }
- if (slide.enterHistogram === 0) estimates.estimateSel.classed('active', 1)
-
-
- // Display the default coin flip state if the histogram is not visible.
- sel.flipCircle.transition().duration(dur)
- .at({transform: d => {
- return slide.showFlipCircle && d.coinVals[estimates.active.index] < sliders.headsProb ? 'scale(1)' : 'scale(.1)'}})
-
- prevSlideIndex = i
- slides.curSlide = slide
- }
-
- var gs = d3.graphScroll()
- .container(d3.select('.container-1'))
- .graph(d3.selectAll('container-1 #graph'))
- .eventId('uniqueId1')
- .sections(d3.selectAll('.container-1 #sections > div'))
- .offset(300)
- .on('active', updateSlide)
-}
-
-
-if (window.init) window.init()
diff --git a/spaces/merve/hidden-bias/source/measuring-diversity/style.css b/spaces/merve/hidden-bias/source/measuring-diversity/style.css
deleted file mode 100644
index 38a1149b1a986d176009fce1d0d2861091ef2c1e..0000000000000000000000000000000000000000
--- a/spaces/merve/hidden-bias/source/measuring-diversity/style.css
+++ /dev/null
@@ -1,229 +0,0 @@
-html{
- min-width: 800px;
- overflow-x: auto;
-}
-
-p{
- max-width: 750px;
- margin-left: 0px auto;
- margin-right: 0px auto;
- margin: 0px auto;
- margin-top: 1em;
- margin-bottom: 1em;
-}
-
-.white{
- stroke: #fff;
- fill: none;
- stroke-width: 1;
-}
-
-.player{
- cursor: pointer;
- stroke: #000;
- stroke-width: 2;
-}
-
-.button{
- border: .5px solid #000;
- /*border-bottom-width: 4px;*/
- /*border-right-width: 4px;*/
- border-radius: 8px;
- padding: 4px;
- margin: 2px;
- cursor: pointer;
- display: inline-block;
- /*font-family: monospace;*/
- /*font-family: 'Roboto Slab', serif;*/
- /*font-size: 16px;*/
- user-select: none;
- font-family: 'Google Sans', sans-serif;
- font-family: 'Roboto', Helvetica, sans-serif;
-
- /*font-weight: 300;*/
-
-}
-.button:hover{
- background: #eee !important;
-}
-
-.button:active{
-}
-
-
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- overflow: visible;
-}
-
-.axis text{
- fill: #999;
- font-family: 'Google Sans', sans-serif;
- font-family: 'Roboto', Helvetica, sans-serif;
-}
-.axis text.chart-title{
- fill: #000;
- font-size: 16px;
-}
-
-.field{
- font-family: 'Roboto', Helvetica, sans-serif;
-}
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-.chart-title span{
- padding: 4px;
-}
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-.shapes{
- line-height: 0px;
- margin-bottom: 80px;
- margin-top: 20px;
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-.shape{
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- outline: 1px solid #bbb;
- margin: 5px;
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-.shape:hover{
- outline: 1px solid #000;
- background: #eee !important;
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-.measure:hover{
- outline: 1px solid #ccc;
- background: #eee !important;
- outline: 1px solid #000 !important;
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-.measure.active{
-}
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- outline: 1px solid #bf0bbf;
- background: rgba(255,0,255,.03);
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-.shape.active:hover{
- background: rgba(255,0,255,.1) !important;
-}
-#all-shapes .shape.active{
- outline: 1px solid #bbb;
- background: #fff;
-}
-
-
-.top, .bot{
- line-height: 1.8em;
-}
-
-.measure{
- cursor: pointer;
- outline: 1px solid #ccc;
- margin: 10px;
-}
-
-.measure-container{
- display:inline-block;
- width: 300px;
- margin-top: 15px;
-}
-
-.measure-description{
- font-size: 14px;
- max-width: 120px;
- line-height: 16px;
- display: inline-block;
-}
-
-.emphasized{
- font-weight: 400;
-}
-
-.set.no-stroke{
- opacity: 0;
-}
-.set{
- stroke: #000;
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-.set.selected{
- stroke: #fcb2f7;
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-.row.selected text{
- opacity: 1 !important;
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-
-text.selected{
- opacity: 1 !important;
- fill: #bf0bbf;
- font-weight: 500;
-
-}
-
-
-
-text{
- /*pointer-events: none;*/
- text-shadow: 0 1px 0 #fff, 1px 0 0 #fff, 0 -1px 0 #fff, -1px 0 0 #fff;
-}
-
-#coat-v-gender, #pick-green, #pick-triangle, #pick-metric, #all-shapes{
- width: 850px;
-}
-#coat-v-gender > div > div{
- background-size: cover;
- background-position: center;
-}
-
-.note, ul{
- opacity: .5;
- max-width: 750px;
- max-width: 750px;
- margin-left: 0px auto;
- margin-right: 0px auto;
- margin: 0px auto;
- margin-top: 1em;
- margin-bottom: 1em;
-
-}
-
-#columns-height {
- margin-bottom: 70px;
-}
-
-.post-summary{
-
- margin-bottom: auto;
-}
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-#all-shapes{
- pointer-events: none;
-}
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-#all-shapes .shape{
- outline: 0px !important;
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-.post-summary{
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-#pick-metric .top text, #coat-v-gender .top text {
- font-weight: 300 !important;
-}
-
diff --git a/spaces/mfrashad/ClothingGAN/netdissect/segmodel/resnet.py b/spaces/mfrashad/ClothingGAN/netdissect/segmodel/resnet.py
deleted file mode 100644
index ea5fdf82fafa3058c5f00074d55fbb1e584d5865..0000000000000000000000000000000000000000
--- a/spaces/mfrashad/ClothingGAN/netdissect/segmodel/resnet.py
+++ /dev/null
@@ -1,235 +0,0 @@
-import os
-import sys
-import torch
-import torch.nn as nn
-import math
-try:
- from lib.nn import SynchronizedBatchNorm2d
-except ImportError:
- from torch.nn import BatchNorm2d as SynchronizedBatchNorm2d
-
-try:
- from urllib import urlretrieve
-except ImportError:
- from urllib.request import urlretrieve
-
-
-__all__ = ['ResNet', 'resnet50', 'resnet101'] # resnet101 is coming soon!
-
-
-model_urls = {
- 'resnet50': 'http://sceneparsing.csail.mit.edu/model/pretrained_resnet/resnet50-imagenet.pth',
- 'resnet101': 'http://sceneparsing.csail.mit.edu/model/pretrained_resnet/resnet101-imagenet.pth'
-}
-
-
-def conv3x3(in_planes, out_planes, stride=1):
- "3x3 convolution with padding"
- return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
- padding=1, bias=False)
-
-
-class BasicBlock(nn.Module):
- expansion = 1
-
- def __init__(self, inplanes, planes, stride=1, downsample=None):
- super(BasicBlock, self).__init__()
- self.conv1 = conv3x3(inplanes, planes, stride)
- self.bn1 = SynchronizedBatchNorm2d(planes)
- self.relu = nn.ReLU(inplace=True)
- self.conv2 = conv3x3(planes, planes)
- self.bn2 = SynchronizedBatchNorm2d(planes)
- self.downsample = downsample
- self.stride = stride
-
- def forward(self, x):
- residual = x
-
- out = self.conv1(x)
- out = self.bn1(out)
- out = self.relu(out)
-
- out = self.conv2(out)
- out = self.bn2(out)
-
- if self.downsample is not None:
- residual = self.downsample(x)
-
- out += residual
- out = self.relu(out)
-
- return out
-
-
-class Bottleneck(nn.Module):
- expansion = 4
-
- def __init__(self, inplanes, planes, stride=1, downsample=None):
- super(Bottleneck, self).__init__()
- self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=1, bias=False)
- self.bn1 = SynchronizedBatchNorm2d(planes)
- self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride,
- padding=1, bias=False)
- self.bn2 = SynchronizedBatchNorm2d(planes)
- self.conv3 = nn.Conv2d(planes, planes * 4, kernel_size=1, bias=False)
- self.bn3 = SynchronizedBatchNorm2d(planes * 4)
- self.relu = nn.ReLU(inplace=True)
- self.downsample = downsample
- self.stride = stride
-
- def forward(self, x):
- residual = x
-
- out = self.conv1(x)
- out = self.bn1(out)
- out = self.relu(out)
-
- out = self.conv2(out)
- out = self.bn2(out)
- out = self.relu(out)
-
- out = self.conv3(out)
- out = self.bn3(out)
-
- if self.downsample is not None:
- residual = self.downsample(x)
-
- out += residual
- out = self.relu(out)
-
- return out
-
-
-class ResNet(nn.Module):
-
- def __init__(self, block, layers, num_classes=1000):
- self.inplanes = 128
- super(ResNet, self).__init__()
- self.conv1 = conv3x3(3, 64, stride=2)
- self.bn1 = SynchronizedBatchNorm2d(64)
- self.relu1 = nn.ReLU(inplace=True)
- self.conv2 = conv3x3(64, 64)
- self.bn2 = SynchronizedBatchNorm2d(64)
- self.relu2 = nn.ReLU(inplace=True)
- self.conv3 = conv3x3(64, 128)
- self.bn3 = SynchronizedBatchNorm2d(128)
- self.relu3 = nn.ReLU(inplace=True)
- self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)
-
- self.layer1 = self._make_layer(block, 64, layers[0])
- self.layer2 = self._make_layer(block, 128, layers[1], stride=2)
- self.layer3 = self._make_layer(block, 256, layers[2], stride=2)
- self.layer4 = self._make_layer(block, 512, layers[3], stride=2)
- self.avgpool = nn.AvgPool2d(7, stride=1)
- self.fc = nn.Linear(512 * block.expansion, num_classes)
-
- for m in self.modules():
- if isinstance(m, nn.Conv2d):
- n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
- m.weight.data.normal_(0, math.sqrt(2. / n))
- elif isinstance(m, SynchronizedBatchNorm2d):
- m.weight.data.fill_(1)
- m.bias.data.zero_()
-
- def _make_layer(self, block, planes, blocks, stride=1):
- downsample = None
- if stride != 1 or self.inplanes != planes * block.expansion:
- downsample = nn.Sequential(
- nn.Conv2d(self.inplanes, planes * block.expansion,
- kernel_size=1, stride=stride, bias=False),
- SynchronizedBatchNorm2d(planes * block.expansion),
- )
-
- layers = []
- layers.append(block(self.inplanes, planes, stride, downsample))
- self.inplanes = planes * block.expansion
- for i in range(1, blocks):
- layers.append(block(self.inplanes, planes))
-
- return nn.Sequential(*layers)
-
- def forward(self, x):
- x = self.relu1(self.bn1(self.conv1(x)))
- x = self.relu2(self.bn2(self.conv2(x)))
- x = self.relu3(self.bn3(self.conv3(x)))
- x = self.maxpool(x)
-
- x = self.layer1(x)
- x = self.layer2(x)
- x = self.layer3(x)
- x = self.layer4(x)
-
- x = self.avgpool(x)
- x = x.view(x.size(0), -1)
- x = self.fc(x)
-
- return x
-
-'''
-def resnet18(pretrained=False, **kwargs):
- """Constructs a ResNet-18 model.
-
- Args:
- pretrained (bool): If True, returns a model pre-trained on Places
- """
- model = ResNet(BasicBlock, [2, 2, 2, 2], **kwargs)
- if pretrained:
- model.load_state_dict(load_url(model_urls['resnet18']))
- return model
-
-
-def resnet34(pretrained=False, **kwargs):
- """Constructs a ResNet-34 model.
-
- Args:
- pretrained (bool): If True, returns a model pre-trained on Places
- """
- model = ResNet(BasicBlock, [3, 4, 6, 3], **kwargs)
- if pretrained:
- model.load_state_dict(load_url(model_urls['resnet34']))
- return model
-'''
-
-def resnet50(pretrained=False, **kwargs):
- """Constructs a ResNet-50 model.
-
- Args:
- pretrained (bool): If True, returns a model pre-trained on Places
- """
- model = ResNet(Bottleneck, [3, 4, 6, 3], **kwargs)
- if pretrained:
- model.load_state_dict(load_url(model_urls['resnet50']), strict=False)
- return model
-
-
-def resnet101(pretrained=False, **kwargs):
- """Constructs a ResNet-101 model.
-
- Args:
- pretrained (bool): If True, returns a model pre-trained on Places
- """
- model = ResNet(Bottleneck, [3, 4, 23, 3], **kwargs)
- if pretrained:
- model.load_state_dict(load_url(model_urls['resnet101']), strict=False)
- return model
-
-# def resnet152(pretrained=False, **kwargs):
-# """Constructs a ResNet-152 model.
-#
-# Args:
-# pretrained (bool): If True, returns a model pre-trained on Places
-# """
-# model = ResNet(Bottleneck, [3, 8, 36, 3], **kwargs)
-# if pretrained:
-# model.load_state_dict(load_url(model_urls['resnet152']))
-# return model
-
-def load_url(url, model_dir='./pretrained', map_location=None):
- if not os.path.exists(model_dir):
- os.makedirs(model_dir)
- filename = url.split('/')[-1]
- cached_file = os.path.join(model_dir, filename)
- if not os.path.exists(cached_file):
- sys.stderr.write('Downloading: "{}" to {}\n'.format(url, cached_file))
- urlretrieve(url, cached_file)
- return torch.load(cached_file, map_location=map_location)
diff --git a/spaces/mipbkhn/BreastCancer/.devcontainer/Dockerfile b/spaces/mipbkhn/BreastCancer/.devcontainer/Dockerfile
deleted file mode 100644
index f9b874fcf80f62572c54f82072784db9d1d627db..0000000000000000000000000000000000000000
--- a/spaces/mipbkhn/BreastCancer/.devcontainer/Dockerfile
+++ /dev/null
@@ -1,5 +0,0 @@
-ARG FROM_IMAGE_NAME=nvcr.io/nvidia/pytorch:22.05-py3
-
-FROM ${FROM_IMAGE_NAME}
-
-RUN pip install fastai nbdev fastbook ipywidgets timm
\ No newline at end of file
diff --git a/spaces/ml6team/semantic-search-demo/README.md b/spaces/ml6team/semantic-search-demo/README.md
deleted file mode 100644
index e2eb3baf070c0ccaa1b2d7b221d565fd7a315936..0000000000000000000000000000000000000000
--- a/spaces/ml6team/semantic-search-demo/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Semantic Search Demo
-emoji: 🦀
-colorFrom: yellow
-colorTo: pink
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/moadams/rainbowRainClassificationAPP/rainbowrain_env/share/jupyter/labextensions/@jupyter-widgets/jupyterlab-manager/static/495.211015baa14adae19b31.js b/spaces/moadams/rainbowRainClassificationAPP/rainbowrain_env/share/jupyter/labextensions/@jupyter-widgets/jupyterlab-manager/static/495.211015baa14adae19b31.js
deleted file mode 100644
index fab690c2c69b552974fa7bda5a3a756343b30203..0000000000000000000000000000000000000000
--- a/spaces/moadams/rainbowRainClassificationAPP/rainbowrain_env/share/jupyter/labextensions/@jupyter-widgets/jupyterlab-manager/static/495.211015baa14adae19b31.js
+++ /dev/null
@@ -1 +0,0 @@
-"use 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i=s(9930);function a(e,t){void 0!==t&&(e.textContent=t),void 0!==window.MathJax&&MathJax.Hub.Queue(["Typeset",MathJax.Hub,e])}function l(e){const t=document.createElement("div");return t.textContent=e,t.innerHTML}function d(e,t){return function(s){throw t&&console.error(new Error(e)),s}}var n=s(61);class o extends i.StyleModel{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"DescriptionStyleModel",_model_module:"@jupyter-widgets/controls",_model_module_version:n.N})}}o.styleProperties={description_width:{selector:".widget-label",attribute:"width",default:null}};class r extends i.DOMWidgetModel{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"DescriptionModel",_view_name:"DescriptionView",_view_module:"@jupyter-widgets/controls",_model_module:"@jupyter-widgets/controls",_view_module_version:n.N,_model_module_version:n.N,description:"",description_allow_html:!1})}}class h extends i.DOMWidgetView{render(){this.label=document.createElement("label"),this.el.appendChild(this.label),this.label.className="widget-label",this.label.style.display="none",this.listenTo(this.model,"change:description",this.updateDescription),this.listenTo(this.model,"change:description_allow_html",this.updateDescription),this.listenTo(this.model,"change:tabbable",this.updateTabindex),this.updateDescription(),this.updateTabindex(),this.updateTooltip()}typeset(e,t){this.displayed.then((()=>a(e,t)))}updateDescription(){const e=this.model.get("description");0===e.length?this.label.style.display="none":(this.model.get("description_allow_html")?this.label.innerHTML=this.model.widget_manager.inline_sanitize(e):this.label.textContent=e,this.typeset(this.label),this.label.style.display="")}updateTooltip(){this.label&&(this.label.title=this.model.get("tooltip"))}}class u extends r{}class c extends h{}class p extends i.WidgetModel{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"CoreWidgetModel",_view_module:"@jupyter-widgets/controls",_model_module:"@jupyter-widgets/controls",_view_module_version:n.N,_model_module_version:n.N})}}class g extends i.DOMWidgetModel{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"CoreDOMWidgetModel",_view_module:"@jupyter-widgets/controls",_model_module:"@jupyter-widgets/controls",_view_module_version:n.N,_model_module_version:n.N})}}class m extends r{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"CoreDescriptionModel",_view_module:"@jupyter-widgets/controls",_model_module:"@jupyter-widgets/controls",_view_module_version:n.N,_model_module_version:n.N})}}class _ extends p{defaults(){return Object.assign(Object.assign({},super.defaults()),{target:void 0,source:void 0,_model_name:"DirectionalLinkModel"})}initialize(e,t){super.initialize(e,t),this.on("change",this.updateBindings,this),this.updateBindings()}updateValue(e,t,s,i){if(!this._updating){this._updating=!0;try{s&&(s.set(i,e.get(t)),s.save_changes())}finally{this._updating=!1}}}updateBindings(){this.cleanup(),[this.sourceModel,this.sourceAttr]=this.get("source")||[null,null],[this.targetModel,this.targetAttr]=this.get("target")||[null,null],this.sourceModel&&(this.listenTo(this.sourceModel,"change:"+this.sourceAttr,(()=>{this.updateValue(this.sourceModel,this.sourceAttr,this.targetModel,this.targetAttr)})),this.updateValue(this.sourceModel,this.sourceAttr,this.targetModel,this.targetAttr),this.listenToOnce(this.sourceModel,"destroy",this.cleanup)),this.targetModel&&this.listenToOnce(this.targetModel,"destroy",this.cleanup)}cleanup(){this.sourceModel&&(this.stopListening(this.sourceModel,"change:"+this.sourceAttr,void 0),this.stopListening(this.sourceModel,"destroy",void 0)),this.targetModel&&this.stopListening(this.targetModel,"destroy",void 0)}}_.serializers=Object.assign(Object.assign({},p.serializers),{target:{deserialize:i.unpack_models},source:{deserialize:i.unpack_models}});class b extends _{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"LinkModel"})}updateBindings(){super.updateBindings(),this.targetModel&&this.listenTo(this.targetModel,"change:"+this.targetAttr,(()=>{this.updateValue(this.targetModel,this.targetAttr,this.sourceModel,this.sourceAttr)}))}cleanup(){super.cleanup(),this.targetModel&&this.stopListening(this.targetModel,"change:"+this.targetAttr,void 0)}}class v extends o{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"CheckboxStyleModel"})}}v.styleProperties=Object.assign(Object.assign({},o.styleProperties),{background:{selector:"",attribute:"background",default:null}});class x extends o{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"ToggleButtonStyleModel"})}}x.styleProperties=Object.assign(Object.assign({},o.styleProperties),{font_family:{selector:"",attribute:"font-family",default:""},font_size:{selector:"",attribute:"font-size",default:""},font_style:{selector:"",attribute:"font-style",default:""},font_variant:{selector:"",attribute:"font-variant",default:""},font_weight:{selector:"",attribute:"font-weight",default:""},text_color:{selector:"",attribute:"color",default:""},text_decoration:{selector:"",attribute:"text-decoration",default:""}});class f extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{value:!1,disabled:!1,_model_name:"BoolModel"})}}class w extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{indent:!0,style:null,_view_name:"CheckboxView",_model_name:"CheckboxModel"})}}class y extends h{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-inline-hbox"),this.el.classList.add("widget-checkbox"),this.label.innerHTML="",this.checkboxLabel=document.createElement("label"),this.checkboxLabel.classList.add("widget-label-basic"),this.el.appendChild(this.checkboxLabel),this.checkbox=document.createElement("input"),this.checkbox.setAttribute("type","checkbox"),this.checkboxLabel.appendChild(this.checkbox),this.descriptionSpan=document.createElement("span"),this.checkboxLabel.appendChild(this.descriptionSpan),this.listenTo(this.model,"change:indent",this.updateIndent),this.listenTo(this.model,"change:tabbable",this.updateTabindex),this.update(),this.updateDescription(),this.updateIndent(),this.updateTabindex(),this.updateTooltip()}updateDescription(){if(null==this.checkboxLabel)return;const e=this.model.get("description");this.model.get("description_allow_html")?this.descriptionSpan.innerHTML=this.model.widget_manager.inline_sanitize(e):this.descriptionSpan.textContent=e,this.typeset(this.descriptionSpan),this.descriptionSpan.title=e,this.checkbox.title=e}updateIndent(){const e=this.model.get("indent");this.label.style.display=e?"":"none"}updateTabindex(){if(!this.checkbox)return;const e=this.model.get("tabbable");!0===e?this.checkbox.setAttribute("tabIndex","0"):!1===e?this.checkbox.setAttribute("tabIndex","-1"):null===e&&this.checkbox.removeAttribute("tabIndex")}updateTooltip(){if(!this.checkbox)return;const e=this.model.get("tooltip");e?0===this.model.get("description").length&&this.checkbox.setAttribute("title",e):this.checkbox.removeAttribute("title")}events(){return{'click input[type="checkbox"]':"_handle_click"}}_handle_click(){const e=this.model.get("value");this.model.set("value",!e,{updated_view:this}),this.touch()}update(e){return this.checkbox.checked=this.model.get("value"),void 0!==e&&e.updated_view==this||(this.checkbox.disabled=this.model.get("disabled")),super.update()}handle_message(e){"focus"==e.do?this.checkbox.focus():"blur"==e.do&&this.checkbox.blur()}}class C extends f{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"ToggleButtonView",_model_name:"ToggleButtonModel",tooltip:"",icon:"",button_style:"",style:null})}}class M extends i.DOMWidgetView{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("jupyter-button"),this.el.classList.add("widget-toggle-button"),this.listenTo(this.model,"change:button_style",this.update_button_style),this.listenTo(this.model,"change:tabbable",this.updateTabindex),this.set_button_style(),this.update()}update_button_style(){this.update_mapped_classes(M.class_map,"button_style")}set_button_style(){this.set_mapped_classes(M.class_map,"button_style")}update(e){if(this.model.get("value")?this.el.classList.add("mod-active"):this.el.classList.remove("mod-active"),void 0===e||e.updated_view!==this){this.el.disabled=this.model.get("disabled"),this.el.setAttribute("tabbable",this.model.get("tabbable")),this.el.setAttribute("title",this.model.get("tooltip"));const e=this.model.get("description"),t=this.model.get("icon");if(0===e.trim().length&&0===t.trim().length)this.el.innerHTML=" ";else{if(this.el.textContent="",t.trim().length){const e=document.createElement("i");this.el.appendChild(e),e.classList.add("fa"),e.classList.add("fa-"+t)}this.el.appendChild(document.createTextNode(e))}}return this.updateTabindex(),super.update()}events(){return{click:"_handle_click"}}_handle_click(e){e.preventDefault();const t=this.model.get("value");this.model.set("value",!t,{updated_view:this}),this.touch()}preinitialize(){this.tagName="button"}}M.class_map={primary:["mod-primary"],success:["mod-success"],info:["mod-info"],warning:["mod-warning"],danger:["mod-danger"]};class j extends f{defaults(){return Object.assign(Object.assign({},super.defaults()),{readout:"Invalid",_view_name:"ValidView",_model_name:"ValidModel"})}}class T extends h{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-valid"),this.el.classList.add("widget-inline-hbox"),this.icon=document.createElement("i"),this.icon.classList.add("fa","fa-fw"),this.el.appendChild(this.icon),this.readout=document.createElement("span"),this.readout.classList.add("widget-valid-readout"),this.readout.classList.add("widget-readout"),this.el.appendChild(this.readout),this.update()}update(){this.el.classList.remove("mod-valid"),this.el.classList.remove("mod-invalid"),this.icon.classList.remove("fa-check"),this.icon.classList.remove("fa-times"),this.readout.textContent=this.model.get("readout"),this.model.get("value")?(this.el.classList.add("mod-valid"),this.icon.classList.add("fa-check")):(this.el.classList.add("mod-invalid"),this.icon.classList.add("fa-times"))}}class S extends i.StyleModel{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"ButtonStyleModel",_model_module:"@jupyter-widgets/controls",_model_module_version:n.N})}}S.styleProperties={button_color:{selector:"",attribute:"background-color",default:null},font_family:{selector:"",attribute:"font-family",default:""},font_size:{selector:"",attribute:"font-size",default:""},font_style:{selector:"",attribute:"font-style",default:""},font_variant:{selector:"",attribute:"font-variant",default:""},font_weight:{selector:"",attribute:"font-weight",default:""},text_color:{selector:"",attribute:"color",default:""},text_decoration:{selector:"",attribute:"text-decoration",default:""}};class O extends g{defaults(){return Object.assign(Object.assign({},super.defaults()),{description:"",tooltip:"",disabled:!1,icon:"",button_style:"",_view_name:"ButtonView",_model_name:"ButtonModel",style:null})}}class k extends i.DOMWidgetView{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("jupyter-button"),this.el.classList.add("widget-button"),this.listenTo(this.model,"change:button_style",this.update_button_style),this.listenTo(this.model,"change:tabbable",this.updateTabindex),this.set_button_style(),this.update()}update(){this.el.disabled=this.model.get("disabled"),this.updateTabindex(),this.el.setAttribute("title",this.model.get("tooltip"));const e=this.model.get("description"),t=this.model.get("icon");if(e.length||t.length){if(this.el.textContent="",t.length){const s=document.createElement("i");s.classList.add("fa"),s.classList.add(...t.split(/[\s]+/).filter(Boolean).map((e=>`fa-${e}`))),0===e.length&&s.classList.add("center"),this.el.appendChild(s)}this.el.appendChild(document.createTextNode(e))}return super.update()}update_button_style(){this.update_mapped_classes(k.class_map,"button_style")}set_button_style(){this.set_mapped_classes(k.class_map,"button_style")}events(){return{click:"_handle_click"}}_handle_click(e){e.preventDefault(),this.send({event:"click"})}preinitialize(){this.tagName="button"}}k.class_map={primary:["mod-primary"],success:["mod-success"],info:["mod-info"],warning:["mod-warning"],danger:["mod-danger"]};var L=s(8918),V=s(2720),I=s(3992),W=s(2994),A=s.n(W);class B extends g{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"BoxView",_model_name:"BoxModel",children:[],box_style:""})}}B.serializers=Object.assign(Object.assign({},g.serializers),{children:{deserialize:i.unpack_models}});class z extends B{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"HBoxView",_model_name:"HBoxModel"})}}class E extends B{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"VBoxView",_model_name:"VBoxModel"})}}class D extends i.DOMWidgetView{_createElement(e){return this.luminoWidget=new i.JupyterLuminoPanelWidget({view:this}),this.luminoWidget.node}_setElement(e){if(this.el||e!==this.luminoWidget.node)throw new Error("Cannot reset the DOM element.");this.el=this.luminoWidget.node,this.$el=A()(this.luminoWidget.node)}initialize(e){super.initialize(e),this.children_views=new i.ViewList(this.add_child_model,null,this),this.listenTo(this.model,"change:children",this.update_children),this.listenTo(this.model,"change:box_style",this.update_box_style),this.luminoWidget.addClass("jupyter-widgets"),this.luminoWidget.addClass("widget-container"),this.luminoWidget.addClass("widget-box")}render(){super.render(),this.update_children(),this.set_box_style()}update_children(){var e;null===(e=this.children_views)||void 0===e||e.update(this.model.get("children")).then((e=>{e.forEach((e=>{V.MessageLoop.postMessage(e.luminoWidget,I.Widget.ResizeMessage.UnknownSize)}))}))}update_box_style(){this.update_mapped_classes(D.class_map,"box_style")}set_box_style(){this.set_mapped_classes(D.class_map,"box_style")}add_child_model(e){const t=new I.Widget;return this.luminoWidget.addWidget(t),this.create_child_view(e).then((e=>{const s=L.ArrayExt.firstIndexOf(this.luminoWidget.widgets,t);return this.luminoWidget.insertWidget(s,e.luminoWidget),t.dispose(),e})).catch((0,i.reject)("Could not add child view to box",!0))}remove(){this.children_views=null,super.remove()}}D.class_map={success:["alert","alert-success"],info:["alert","alert-info"],warning:["alert","alert-warning"],danger:["alert","alert-danger"]};class P extends D{initialize(e){super.initialize(e),this.luminoWidget.addClass("widget-hbox")}}class F extends D{initialize(e){super.initialize(e),this.luminoWidget.addClass("widget-vbox")}}class U extends D{initialize(e){super.initialize(e),this.luminoWidget.addClass("widget-gridbox"),this.luminoWidget.removeClass("widget-box")}}class R extends B{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"GridBoxView",_model_name:"GridBoxModel"})}}class N extends g{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"ImageModel",_view_name:"ImageView",format:"png",width:"",height:"",value:new DataView(new ArrayBuffer(0))})}}N.serializers=Object.assign(Object.assign({},g.serializers),{value:{serialize:e=>new DataView(e.buffer.slice(0))}});class $ extends i.DOMWidgetView{render(){super.render(),this.luminoWidget.addClass("jupyter-widgets"),this.luminoWidget.addClass("widget-image"),this.update()}update(){let e;const t=this.model.get("format"),s=this.model.get("value");if("url"!==t){const t=new Blob([s],{type:`image/${this.model.get("format")}`});e=URL.createObjectURL(t)}else e=new TextDecoder("utf-8").decode(s.buffer);const i=this.el.src;this.el.src=e,i&&URL.revokeObjectURL(i);const a=this.model.get("width");void 0!==a&&a.length>0?this.el.setAttribute("width",a):this.el.removeAttribute("width");const l=this.model.get("height");return void 0!==l&&l.length>0?this.el.setAttribute("height",l):this.el.removeAttribute("height"),super.update()}remove(){this.el.src&&URL.revokeObjectURL(this.el.src),super.remove()}preinitialize(){this.tagName="img"}}class H extends g{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"VideoModel",_view_name:"VideoView",format:"mp4",width:"",height:"",autoplay:!0,loop:!0,controls:!0,value:new DataView(new ArrayBuffer(0))})}}H.serializers=Object.assign(Object.assign({},g.serializers),{value:{serialize:e=>new DataView(e.buffer.slice(0))}});class K extends i.DOMWidgetView{render(){super.render(),this.luminoWidget.addClass("jupyter-widgets"),this.luminoWidget.addClass("widget-image"),this.update()}update(){let e;const t=this.model.get("format"),s=this.model.get("value");if("url"!==t){const t=new Blob([s],{type:`video/${this.model.get("format")}`});e=URL.createObjectURL(t)}else e=new TextDecoder("utf-8").decode(s.buffer);const i=this.el.src;this.el.src=e,i&&URL.revokeObjectURL(i);const a=this.model.get("width");void 0!==a&&a.length>0?this.el.setAttribute("width",a):this.el.removeAttribute("width");const l=this.model.get("height");return void 0!==l&&l.length>0?this.el.setAttribute("height",l):this.el.removeAttribute("height"),this.el.loop=this.model.get("loop"),this.el.autoplay=this.model.get("autoplay"),this.el.controls=this.model.get("controls"),super.update()}remove(){this.el.src&&URL.revokeObjectURL(this.el.src),super.remove()}preinitialize(){this.tagName="video"}}class q extends g{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"AudioModel",_view_name:"AudioView",format:"mp3",autoplay:!0,loop:!0,controls:!0,value:new DataView(new ArrayBuffer(0))})}}q.serializers=Object.assign(Object.assign({},g.serializers),{value:{serialize:e=>new DataView(e.buffer.slice(0))}});class G extends i.DOMWidgetView{render(){super.render(),this.luminoWidget.addClass("jupyter-widgets"),this.update()}update(){let e;const t=this.model.get("format"),s=this.model.get("value");if("url"!==t){const t=new Blob([s],{type:`audio/${this.model.get("format")}`});e=URL.createObjectURL(t)}else e=new TextDecoder("utf-8").decode(s.buffer);const i=this.el.src;return this.el.src=e,i&&URL.revokeObjectURL(i),this.el.loop=this.model.get("loop"),this.el.autoplay=this.model.get("autoplay"),this.el.controls=this.model.get("controls"),super.update()}remove(){this.el.src&&URL.revokeObjectURL(this.el.src),super.remove()}preinitialize(){this.tagName="audio"}}const J={aliceblue:"#f0f8ff",antiquewhite:"#faebd7",aqua:"#00ffff",aquamarine:"#7fffd4",azure:"#f0ffff",beige:"#f5f5dc",bisque:"#ffe4c4",black:"#000000",blanchedalmond:"#ffebcd",blue:"#0000ff",blueviolet:"#8a2be2",brown:"#a52a2a",burlywood:"#deb887",cadetblue:"#5f9ea0",chartreuse:"#7fff00",chocolate:"#d2691e",coral:"#ff7f50",cornflowerblue:"#6495ed",cornsilk:"#fff8dc",crimson:"#dc143c",cyan:"#00ffff",darkblue:"#00008b",darkcyan:"#008b8b",darkgoldenrod:"#b8860b",darkgray:"#a9a9a9",darkgrey:"#a9a9a9",darkgreen:"#006400",darkkhaki:"#bdb76b",darkmagenta:"#8b008b",darkolivegreen:"#556b2f",darkorange:"#ff8c00",darkorchid:"#9932cc",darkred:"#8b0000",darksalmon:"#e9967a",darkseagreen:"#8fbc8f",darkslateblue:"#483d8b",darkslategray:"#2f4f4f",darkslategrey:"#2f4f4f",darkturquoise:"#00ced1",darkviolet:"#9400d3",deeppink:"#ff1493",deepskyblue:"#00bfff",dimgray:"#696969",dimgrey:"#696969",dodgerblue:"#1e90ff",firebrick:"#b22222",floralwhite:"#fffaf0",forestgreen:"#228b22",fuchsia:"#ff00ff",gainsboro:"#dcdcdc",ghostwhite:"#f8f8ff",gold:"#ffd700",goldenrod:"#daa520",gray:"#808080",grey:"#808080",green:"#008000",greenyellow:"#adff2f",honeydew:"#f0fff0",hotpink:"#ff69b4",indianred:"#cd5c5c",indigo:"#4b0082",ivory:"#fffff0",khaki:"#f0e68c",lavender:"#e6e6fa",lavenderblush:"#fff0f5",lawngreen:"#7cfc00",lemonchiffon:"#fffacd",lightblue:"#add8e6",lightcoral:"#f08080",lightcyan:"#e0ffff",lightgoldenrodyellow:"#fafad2",lightgreen:"#90ee90",lightgray:"#d3d3d3",lightgrey:"#d3d3d3",lightpink:"#ffb6c1",lightsalmon:"#ffa07a",lightseagreen:"#20b2aa",lightskyblue:"#87cefa",lightslategray:"#778899",lightslategrey:"#778899",lightsteelblue:"#b0c4de",lightyellow:"#ffffe0",lime:"#00ff00",limegreen:"#32cd32",linen:"#faf0e6",magenta:"#ff00ff",maroon:"#800000",mediumaquamarine:"#66cdaa",mediumblue:"#0000cd",mediumorchid:"#ba55d3",mediumpurple:"#9370db",mediumseagreen:"#3cb371",mediumslateblue:"#7b68ee",mediumspringgreen:"#00fa9a",mediumturquoise:"#48d1cc",mediumvioletred:"#c71585",midnightblue:"#191970",mintcream:"#f5fffa",mistyrose:"#ffe4e1",moccasin:"#ffe4b5",navajowhite:"#ffdead",navy:"#000080",oldlace:"#fdf5e6",olive:"#808000",olivedrab:"#6b8e23",orange:"#ffa500",orangered:"#ff4500",orchid:"#da70d6",palegoldenrod:"#eee8aa",palegreen:"#98fb98",paleturquoise:"#afeeee",palevioletred:"#db7093",papayawhip:"#ffefd5",peachpuff:"#ffdab9",peru:"#cd853f",pink:"#ffc0cb",plum:"#dda0dd",powderblue:"#b0e0e6",purple:"#800080",red:"#ff0000",rosybrown:"#bc8f8f",royalblue:"#4169e1",saddlebrown:"#8b4513",salmon:"#fa8072",sandybrown:"#f4a460",seagreen:"#2e8b57",seashell:"#fff5ee",sienna:"#a0522d",silver:"#c0c0c0",skyblue:"#87ceeb",slateblue:"#6a5acd",slategray:"#708090",slategrey:"#708090",snow:"#fffafa",springgreen:"#00ff7f",steelblue:"#4682b4",tan:"#d2b48c",teal:"#008080",thistle:"#d8bfd8",tomato:"#ff6347",turquoise:"#40e0d0",violet:"#ee82ee",wheat:"#f5deb3",white:"#ffffff",whitesmoke:"#f5f5f5",yellow:"#ffff00",yellowgreen:"#9acd32"};class Y extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{value:"black",concise:!1,_model_name:"ColorPickerModel",_view_name:"ColorPickerView"})}}class Z extends h{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-inline-hbox"),this.el.classList.add("widget-colorpicker"),this._color_container=document.createElement("div"),this._color_container.className="widget-inline-hbox widget-colorpicker-input",this.el.appendChild(this._color_container),this._textbox=document.createElement("input"),this._textbox.setAttribute("type","text"),this._textbox.id=this.label.htmlFor=(0,i.uuid)(),this._color_container.appendChild(this._textbox),this._textbox.value=this.model.get("value"),this._colorpicker=document.createElement("input"),this._colorpicker.setAttribute("type","color"),this._color_container.appendChild(this._colorpicker),this.listenTo(this.model,"change:value",this._update_value),this.listenTo(this.model,"change:concise",this._update_concise),this._update_concise(),this._update_value(),this.update()}update(e){if(void 0===e||e.updated_view!=this){const e=this.model.get("disabled");this._textbox.disabled=e,this._colorpicker.disabled=e}return super.update()}events(){return this._picker_change,this._text_change,{'change [type="color"]':"_picker_change",'change [type="text"]':"_text_change"}}_update_value(){const e=this.model.get("value");var t,s;this._colorpicker.value=J[(t=e).toLowerCase()]||(7===(s=t).length?s:"#"+s.charAt(1)+s.charAt(1)+s.charAt(2)+s.charAt(2)+s.charAt(3)+s.charAt(3)),this._textbox.value=e}_update_concise(){this.model.get("concise")?(this.el.classList.add("concise"),this._textbox.style.display="none"):(this.el.classList.remove("concise"),this._textbox.style.display="")}_picker_change(){this.model.set("value",this._colorpicker.value),this.touch()}_text_change(){const e=this._validate_color(this._textbox.value,this.model.get("value"));this.model.set("value",e),this.touch()}_validate_color(e,t){return e.match(/#[a-fA-F0-9]{3}(?:[a-fA-F0-9]{3})?$/)||J[e.toLowerCase()]?e:t}}function Q(e){return null===e?null:{year:e.getUTCFullYear(),month:e.getUTCMonth(),date:e.getUTCDate()}}function X(e){if(null===e)return null;{const t=new Date;return t.setUTCFullYear(e.year,e.month,e.date),t.setUTCHours(0,0,0,0),t}}class ee extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{value:null,_model_name:"DatePickerModel",_view_name:"DatePickerView"})}}ee.serializers=Object.assign(Object.assign({},m.serializers),{value:{serialize:Q,deserialize:X}});class te extends h{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-inline-hbox"),this.el.classList.add("widget-datepicker"),this._datepicker=document.createElement("input"),this._datepicker.setAttribute("type","date"),this._datepicker.id=this.label.htmlFor=(0,i.uuid)(),this.el.appendChild(this._datepicker),this.listenTo(this.model,"change:value",this._update_value),this._update_value(),this.update()}update(e){return void 0!==e&&e.updated_view===this||(this._datepicker.disabled=this.model.get("disabled")),super.update()}events(){return this._picker_change,this._picker_focusout,{'change [type="date"]':"_picker_change",'focusout [type="date"]':"_picker_focusout"}}_update_value(){const e=this.model.get("value");this._datepicker.valueAsDate=e}_picker_change(){this._datepicker.validity.badInput||(this.model.set("value",this._datepicker.valueAsDate),this.touch())}_picker_focusout(){this._datepicker.validity.badInput&&(this.model.set("value",null),this.touch())}}const se=/(\d\d):(\d\d)(:(\d\d)(.(\d{1,3})\d*)?)?/;function ie(e){if(null===e)return null;{const t=se.exec(e);return null===t?null:{hours:Math.min(23,parseInt(t[1],10)),minutes:Math.min(59,parseInt(t[2],10)),seconds:t[4]?Math.min(59,parseInt(t[4],10)):0,milliseconds:t[6]?parseInt(t[6],10):0}}}function ae(e){if(null===e)return null;{const t=[`${e.hours.toString().padStart(2,"0")}:${e.minutes.toString().padStart(2,"0")}`];return(e.seconds>0||e.milliseconds>0)&&(t.push(`:${e.seconds.toString().padStart(2,"0")}`),e.milliseconds>0&&t.push(`.${e.milliseconds.toString().padStart(3,"0")}`)),t.join("")}}const le={serialize:ie,deserialize:ae};class de extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:de.model_name,_view_name:de.view_name,value:null,disabled:!1,min:null,max:null,step:60})}}de.serializers=Object.assign(Object.assign({},m.serializers),{value:le,min:le,max:le}),de.model_name="TimeModel",de.view_name="TimeView";class ne extends h{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-inline-hbox"),this.el.classList.add("widget-timepicker"),this._timepicker=document.createElement("input"),this._timepicker.setAttribute("type","time"),this._timepicker.id=this.label.htmlFor=(0,i.uuid)(),this.el.appendChild(this._timepicker),this.listenTo(this.model,"change:value",this._update_value),this.listenTo(this.model,"change",this.update2),this._update_value(),this.update2()}update2(e,t){return void 0!==t&&t.updated_view===this||(this._timepicker.disabled=this.model.get("disabled"),this._timepicker.min=this.model.get("min"),this._timepicker.max=this.model.get("max"),this._timepicker.step=this.model.get("step")),super.update()}events(){return this._picker_change,this._picker_focusout,{'change [type="time"]':"_picker_change",'focusout [type="time"]':"_picker_focusout"}}_update_value(e,t,s){void 0!==s&&s.updated_view===this||(this._timepicker.value=this.model.get("value"))}_picker_change(){this._timepicker.validity.badInput||(this.model.set("value",this._timepicker.value,{updated_view:this}),this.touch())}_picker_focusout(){this._timepicker.validity.badInput&&(this.model.set("value",null,{updated_view:this}),this.touch())}}function oe(e){return null===e?null:{year:e.getUTCFullYear(),month:e.getUTCMonth(),date:e.getUTCDate(),hours:e.getUTCHours(),minutes:e.getUTCMinutes(),seconds:e.getUTCSeconds(),milliseconds:e.getUTCMilliseconds()}}function re(e){if(null===e)return null;{const t=new Date;return t.setUTCFullYear(e.year,e.month,e.date),t.setUTCHours(e.hours,e.minutes,e.seconds,e.milliseconds),t}}const he={serialize:oe,deserialize:re};class ue extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"DatetimeModel",_view_name:"DatetimeView",value:null,disabled:!1,min:null,max:null})}}ue.serializers=Object.assign(Object.assign({},m.serializers),{value:he,min:he,max:he});class ce extends h{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-inline-hbox"),this.el.classList.add("widget-datetimepicker");const e=document.createElement("input");e.type="datetime-local","text"===e.type?(this._datepicker=document.createElement("input"),this._datepicker.setAttribute("type","date"),this._datepicker.id=this.label.htmlFor=(0,i.uuid)(),this._timepicker=document.createElement("input"),this._timepicker.setAttribute("type","time"),this._timepicker.id=(0,i.uuid)(),this.el.appendChild(this._datepicker),this.el.appendChild(this._timepicker)):(this._datetimepicker=e,this._datetimepicker.id=this.label.htmlFor=(0,i.uuid)(),this.el.appendChild(this._datetimepicker)),this.listenTo(this.model,"change:value",this._update_value),this.listenTo(this.model,"change",this.update2),this._update_value(),this.update2()}update2(e,t){if(void 0===t||t.updated_view!==this){const e=this.model.get("min"),t=this.model.get("max");this._datetimepicker?(this._datetimepicker.disabled=this.model.get("disabled"),this._datetimepicker.min=pe.dt_as_dt_string(e),this._datetimepicker.max=pe.dt_as_dt_string(t)):(this._datepicker.disabled=this.model.get("disabled"),this._datepicker.min=pe.dt_as_date_string(e),this._datepicker.max=pe.dt_as_date_string(t),this._timepicker.disabled=this.model.get("disabled"))}}events(){return this._picker_change,this._picker_focusout,{'change [type="date"]':"_picker_change",'change [type="time"]':"_picker_change",'change [type="datetime-local"]':"_picker_change",'focusout [type="date"]':"_picker_focusout",'focusout [type="datetime-local"]':"_picker_focusout",'focusout [type="time"]':"_picker_focusout"}}_update_value(e,t,s){if(void 0===s||s.updated_view!==this){const e=this.model.get("value");this._datetimepicker?this._datetimepicker.value=pe.dt_as_dt_string(e):(this._datepicker.valueAsDate=e,this._timepicker.value=pe.dt_as_time_string(e))}}_picker_change(){if(this._datetimepicker){if(!this._datetimepicker.validity.badInput){const e=this._datetimepicker.value;let t=e?new Date(e):null;t&&isNaN(t.valueOf())&&(t=null),this.model.set("value",t,{updated_view:this}),this.touch()}}else if(!this._datepicker.validity.badInput&&!this._timepicker.validity.badInput){const e=this._datepicker.valueAsDate,t=ie(this._timepicker.value);null!==e&&null!==t&&e.setHours(t.hours,t.minutes,t.seconds,t.milliseconds),this.model.set("value",null!==t&&e,{updated_view:this}),this.touch()}}_picker_focusout(){[this._datetimepicker,this._datepicker,this._timepicker].some((e=>e&&e.validity.badInput))&&(this.model.set("value",null),this.touch())}}var pe;function ge(e){return null===e?null:{year:e.getFullYear(),month:e.getMonth(),date:e.getDate(),hours:e.getHours(),minutes:e.getMinutes(),seconds:e.getSeconds(),milliseconds:e.getMilliseconds()}}function me(e){if(null===e)return null;{const t=new Date;return t.setFullYear(e.year,e.month,e.date),t.setHours(e.hours,e.minutes,e.seconds,e.milliseconds),t}}!function(e){function t(e){if(null===e)return"";const t=[];return t.push(`${e.getFullYear().toString().padStart(4,"0")}`),t.push(`-${(e.getMonth()+1).toString().padStart(2,"0")}`),t.push(`-${e.getDate().toString().padStart(2,"0")}`),t.push(`T${e.getHours().toString().padStart(2,"0")}`),t.push(`:${e.getMinutes().toString().padStart(2,"0")}`),(e.getSeconds()>0||e.getMilliseconds()>0)&&(t.push(`:${e.getSeconds().toString().padStart(2,"0")}`),e.getMilliseconds()>0&&t.push(`.${e.getMilliseconds().toString().padStart(3,"0")}`)),t.join("")}e.dt_as_dt_string=t,e.dt_as_date_string=function(e){return e?t(e).split("T",2)[0]:""},e.dt_as_time_string=function(e){return e?t(e).split("T",2)[1]:""}}(pe||(pe={}));const _e={serialize:ge,deserialize:me};class be extends ue{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"NaiveDatetimeModel"})}}be.serializers=Object.assign(Object.assign({},m.serializers),{value:_e,min:_e,max:_e});var ve=s(4359),xe=s(6547),fe=s.n(xe);class we extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"IntModel",value:0})}}class ye extends we{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"BoundedIntModel",max:100,min:0})}}class Ce extends o{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"SliderStyleModel"})}}Ce.styleProperties=Object.assign(Object.assign({},o.styleProperties),{handle_color:{selector:".noUi-handle",attribute:"background-color",default:null}});class Me extends ye{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"IntSliderModel",_view_name:"IntSliderView",step:1,orientation:"horizontal",readout:!0,readout_format:"d",continuous_update:!0,style:null,disabled:!1})}initialize(e,t){super.initialize(e,t),this.on("change:readout_format",this.update_readout_format,this),this.update_readout_format()}update_readout_format(){this.readout_formatter=(0,ve.WU)(this.get("readout_format"))}}class je extends Me{}class Te extends h{constructor(){super(...arguments),this._parse_value=parseInt}render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-inline-hbox"),this.el.classList.add("widget-slider"),this.el.classList.add("widget-hslider"),this.$slider=document.createElement("div"),this.$slider.classList.add("slider"),this.slider_container=document.createElement("div"),this.slider_container.classList.add("slider-container"),this.slider_container.appendChild(this.$slider),this.el.appendChild(this.slider_container),this.readout=document.createElement("div"),this.el.appendChild(this.readout),this.readout.classList.add("widget-readout"),this.readout.contentEditable="true",this.readout.style.display="none",this.createSlider(),this.model.on("change:orientation",this.regenSlider,this),this.model.on("change:max",this.updateSliderOptions,this),this.model.on("change:min",this.updateSliderOptions,this),this.model.on("change:step",this.updateSliderOptions,this),this.model.on("change:value",this.updateSliderValue,this),this.update()}update(e){return void 0!==e&&e.updated_view===this||(this.model.get("disabled")?(this.readout.contentEditable="false",this.$slider.setAttribute("disabled",!0)):(this.readout.contentEditable="true",this.$slider.removeAttribute("disabled")),"vertical"===this.model.get("orientation")?(this.el.classList.remove("widget-hslider"),this.el.classList.add("widget-vslider"),this.el.classList.remove("widget-inline-hbox"),this.el.classList.add("widget-inline-vbox")):(this.el.classList.remove("widget-vslider"),this.el.classList.add("widget-hslider"),this.el.classList.remove("widget-inline-vbox"),this.el.classList.add("widget-inline-hbox")),this.model.get("readout")?(this.readout.style.display="",this.displayed.then((()=>{this.readout_overflow()?this.readout.classList.add("overflow"):this.readout.classList.remove("overflow")}))):this.readout.style.display="none"),super.update()}readout_overflow(){return this.readout.scrollWidth>this.readout.clientWidth}events(){return{"blur [contentEditable=true]":"handleTextChange","keydown [contentEditable=true]":"handleKeyDown"}}handleKeyDown(e){13===e.keyCode&&(e.preventDefault(),this.handleTextChange())}createSlider(){const e=this.model.get("orientation"),t=this.model.get("behavior");fe().create(this.$slider,{start:this.model.get("value"),connect:!0,behaviour:t,range:{min:this.model.get("min"),max:this.model.get("max")},step:this.model.get("step"),animate:!1,orientation:e,direction:"horizontal"===e?"ltr":"rtl",format:{from:e=>Number(e),to:e=>this._validate_slide_value(e)}}),this.$slider.noUiSlider.on("update",((e,t)=>{this.handleSliderChange(e,t)})),this.$slider.noUiSlider.on("end",((e,t)=>{this.handleSliderChanged(e,t)}))}regenSlider(e){this.$slider.noUiSlider.destroy(),this.createSlider()}_validate_slide_value(e){return Math.round(e)}}class Se extends Te{constructor(){super(...arguments),this._range_regex=/^\s*([+-]?\d+)\s*[-:–]\s*([+-]?\d+)/}update(e){super.update(e);const t=this.model.get("value");this.readout.textContent=this.valueToString(t),this.model.get("value")!==t&&(this.model.set("value",t,{updated_view:this}),this.touch())}valueToString(e){const t=this.model.readout_formatter;return e.map((function(e){return t(e)})).join(" – ")}stringToValue(e){if(null===e)return null;const t=this._range_regex.exec(e);return t?[this._parse_value(t[1]),this._parse_value(t[2])]:null}handleTextChange(){let e=this.stringToValue(this.readout.textContent);const t=this.model.get("min"),s=this.model.get("max");null===e||isNaN(e[0])||isNaN(e[1])||e[0]>e[1]?this.readout.textContent=this.valueToString(this.model.get("value")):(e=[Math.max(Math.min(e[0],s),t),Math.max(Math.min(e[1],s),t)],e[0]!==this.model.get("value")[0]||e[1]!==this.model.get("value")[1]?(this.readout.textContent=this.valueToString(e),this.model.set("value",e),this.touch()):this.readout.textContent=this.valueToString(this.model.get("value")))}handleSliderChange(e,t){const s=e.map(this._validate_slide_value);this.readout.textContent=this.valueToString(s),this.model.get("continuous_update")&&this.handleSliderChanged(e,t)}handleSliderChanged(e,t){const s=e.map(this._validate_slide_value);this.model.set("value",s,{updated_view:this}),this.touch()}updateSliderOptions(e){this.$slider.noUiSlider.updateOptions({start:this.model.get("value"),range:{min:this.model.get("min"),max:this.model.get("max")},step:this.model.get("step")})}updateSliderValue(e,t,s){if(s.updated_view===this)return;const i=this.$slider.noUiSlider.get(),a=this.model.get("value");i[0]===a[0]&&i[1]===a[1]||this.$slider.noUiSlider.set(a)}}class Oe extends Te{update(e){super.update(e);const t=this.model.get("min"),s=this.model.get("max");let i=this.model.get("value");i>s?i=s:ithis.max&&(this.dx=this.max-this.start),this.start+this.dx<0&&(this.dx=-this.start)}}class Ft extends g{defaults(){return Object.assign(Object.assign({},super.defaults()),{value:[],placeholder:"",allowed_tags:null,allow_duplicates:!0})}}class Ut extends i.DOMWidgetView{constructor(){super(...arguments),this.hoveredTag=null,this.hoveredTagIndex=null}render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("jupyter-widget-tagsinput"),this.taginputWrapper=document.createElement("div"),this.model.get("value").length?this.taginputWrapper.style.display="none":this.taginputWrapper.style.display="inline-block",this.datalistID=(0,i.uuid)(),this.taginput=document.createElement("input"),this.taginput.classList.add("jupyter-widget-tag"),this.taginput.classList.add("jupyter-widget-taginput"),this.taginput.setAttribute("list",this.datalistID),this.taginput.setAttribute("type","text"),this.autocompleteList=document.createElement("datalist"),this.autocompleteList.id=this.datalistID,this.updateAutocomplete(),this.model.on("change:allowed_tags",this.updateAutocomplete.bind(this)),this.updatePlaceholder(),this.model.on("change:placeholder",this.updatePlaceholder.bind(this)),this.taginputWrapper.classList.add("widget-text"),this.taginputWrapper.appendChild(this.taginput),this.taginputWrapper.appendChild(this.autocompleteList),this.el.onclick=this.focus.bind(this),this.el.ondrop=e=>{const t=null==this.hoveredTagIndex?this.tags.length:this.hoveredTagIndex;return this.ondrop(e,t)},this.el.ondragover=this.ondragover.bind(this),this.taginput.onchange=this.handleValueAdded.bind(this),this.taginput.oninput=this.resizeInput.bind(this),this.taginput.onkeydown=this.handleKeyEvent.bind(this),this.taginput.onblur=this.loseFocus.bind(this),this.resizeInput(),this.inputIndex=this.model.get("value").length,this.selection=null,this.preventLoosingFocus=!1,this.update()}update(){this.preventLoosingFocus=!0,Dt(this.el),this.tags=[];const e=this.model.get("value");for(const t in e){const s=parseInt(t),i=this.createTag(e[s],s,null!=this.selection&&this.selection.isSelected(s));i.draggable=!0,i.ondragstart=((e,t)=>s=>{this.ondragstart(s,e,t,this.model.model_id)})(s,e[s]),i.ondrop=(e=>t=>{this.ondrop(t,e)})(s),i.ondragover=this.ondragover.bind(this),i.ondragenter=(e=>t=>{this.ondragenter(t,e)})(s),i.ondragend=this.ondragend.bind(this),this.tags.push(i),this.el.appendChild(i)}return this.el.insertBefore(this.taginputWrapper,this.el.children[this.inputIndex]),this.model.get("value").length?this.taginputWrapper.style.display="none":this.taginputWrapper.style.display="inline-block",this.preventLoosingFocus=!1,super.update()}updateAutocomplete(){Dt(this.autocompleteList);const e=this.model.get("allowed_tags");for(const t of e){const e=document.createElement("option");e.value=t,this.autocompleteList.appendChild(e)}}updatePlaceholder(){this.taginput.placeholder=this.model.get("placeholder"),this.resizeInput()}updateTags(){const e=this.model.get("value");for(const t in this.tags){const s=parseInt(t);this.updateTag(this.tags[s],e[s],s,null!=this.selection&&this.selection.isSelected(s))}}handleValueAdded(e){const t=this.taginput.value.replace(/^\s+|\s+$/g,""),s=this.inputIndex;""!=t&&(this.inputIndex++,this.addTag(s,t)&&(this.taginput.value="",this.resizeInput(),this.focus()))}addTag(e,t){const s=this.model.get("value");let i;try{i=this.validateValue(t)}catch(e){return!1}const a=this.model.get("allowed_tags");if(a.length&&!a.includes(i))return!1;if(!this.model.get("allow_duplicates")&&s.includes(i))return!1;this.selection=null;const l=[...s];return l.splice(e,0,i),this.model.set("value",l),this.model.save_changes(),!0}resizeInput(){let e;e=0!=this.taginput.value.length?this.taginput.value:this.model.get("placeholder");const t=e.length+1;this.taginput.setAttribute("size",String(t))}handleKeyEvent(e){const t=this.model.get("value").length;if(this.taginput.value.length)return;const s=this.inputIndex;switch(e.key){case"ArrowLeft":e.ctrlKey&&e.shiftKey&&this.select(s,-s),!e.ctrlKey&&e.shiftKey&&this.select(s,-1),e.ctrlKey?this.inputIndex=0:this.inputIndex--;break;case"ArrowRight":e.ctrlKey&&e.shiftKey&&this.select(s,t-s),!e.ctrlKey&&e.shiftKey&&this.select(s,1),e.ctrlKey?this.inputIndex=t:this.inputIndex++;break;case"Backspace":this.selection?this.removeSelectedTags():this.removeTag(this.inputIndex-1);break;case"Delete":this.selection?this.removeSelectedTags():this.removeTag(this.inputIndex);break;default:return}var i,a;e.shiftKey||(this.selection=null),this.inputIndex=(i=this.inputIndex,0,a=t,Math.min(Math.max(i,0),a)),this.update(),this.focus()}ondragstart(e,t,s,i){null!=e.dataTransfer&&(e.dataTransfer.setData("index",String(t)),e.dataTransfer.setData("tagValue",String(s)),e.dataTransfer.setData("origin",i))}ondrop(e,t){if(null==e.dataTransfer)return;e.preventDefault(),e.stopPropagation();const s=e.dataTransfer.getData("tagValue"),i=parseInt(e.dataTransfer.getData("index")),a=e.dataTransfer.getData("origin")==this.model.model_id;if(!isNaN(i)){if(a){const e=[...this.model.get("value")];return ii)throw e+" is not a valid number, it should be in the range ["+s+", "+i+"]";return t}}class Gt extends Kt{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"FloatsInputView",_model_name:"FloatsInputModel",format:".1f"})}}class Jt extends qt{parseNumber(e){return parseFloat(e)}}class Yt extends Kt{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"IntsInputView",_model_name:"IntsInputModel",format:"d"})}}class Zt extends qt{parseNumber(e){const t=parseInt(e);if(t!=parseFloat(e))throw e+" should be an integer";return t}}class Qt extends o{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"StringStyleModel",_model_module:"@jupyter-widgets/controls",_model_module_version:n.N})}}Qt.styleProperties=Object.assign(Object.assign({},o.styleProperties),{background:{selector:"",attribute:"background",default:null},font_size:{selector:"",attribute:"font-size",default:""},text_color:{selector:"",attribute:"color",default:""}});class Xt extends Qt{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"HTMLStyleModel",_model_module:"@jupyter-widgets/controls",_model_module_version:n.N})}}Xt.styleProperties=Object.assign({},Qt.styleProperties);class es extends Qt{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"HTMLMathStyleModel",_model_module:"@jupyter-widgets/controls",_model_module_version:n.N})}}es.styleProperties=Object.assign({},Qt.styleProperties);class ts extends Qt{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"LabelStyleModel",_model_module:"@jupyter-widgets/controls",_model_module_version:n.N})}}ts.styleProperties=Object.assign(Object.assign({},Qt.styleProperties),{font_family:{selector:"",attribute:"font-family",default:""},font_style:{selector:"",attribute:"font-style",default:""},font_variant:{selector:"",attribute:"font-variant",default:""},font_weight:{selector:"",attribute:"font-weight",default:""},text_decoration:{selector:"",attribute:"text-decoration",default:""}});class ss extends o{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"TextStyleModel",_model_module:"@jupyter-widgets/controls",_model_module_version:n.N})}}ss.styleProperties=Object.assign(Object.assign({},o.styleProperties),{background:{selector:".widget-input",attribute:"background",default:null},font_size:{selector:".widget-input",attribute:"font-size",default:""},text_color:{selector:".widget-input",attribute:"color",default:""}});class is extends m{defaults(){return Object.assign(Object.assign({},super.defaults()),{value:"",disabled:!1,placeholder:"",_model_name:"StringModel"})}}class as extends h{render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-inline-hbox")}}class ls extends is{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"HTMLView",_model_name:"HTMLModel"})}}class ds extends as{render(){super.render(),this.el.classList.add("widget-html"),this.content=document.createElement("div"),this.content.classList.add("widget-html-content"),this.el.appendChild(this.content),this.update()}update(){return this.content.innerHTML=this.model.get("value"),super.update()}handle_message(e){"focus"===e.do?this.content.focus():"blur"===e.do&&this.content.blur()}}class ns extends is{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"HTMLMathView",_model_name:"HTMLMathModel"})}}class os extends as{render(){super.render(),this.el.classList.add("widget-htmlmath"),this.content=document.createElement("div"),this.content.classList.add("widget-htmlmath-content"),this.el.appendChild(this.content),this.update()}update(){return this.content.innerHTML=this.model.get("value"),this.typeset(this.content),super.update()}handle_message(e){"focus"===e.do?this.content.focus():"blur"===e.do&&this.content.blur()}}class rs extends is{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"LabelView",_model_name:"LabelModel"})}}class hs extends as{render(){super.render(),this.el.classList.add("widget-label"),this.update()}update(){return this.typeset(this.el,this.model.get("value")),super.update()}}class us extends is{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"TextareaView",_model_name:"TextareaModel",rows:null,continuous_update:!0})}}class cs extends as{render(){super.render(),this.el.classList.add("widget-textarea"),this.textbox=document.createElement("textarea"),this.textbox.setAttribute("rows","5"),this.textbox.id=this.label.htmlFor=(0,i.uuid)(),this.textbox.classList.add("widget-input"),this.el.appendChild(this.textbox),this.update(),this.listenTo(this.model,"change:placeholder",((e,t,s)=>{this.update_placeholder(t)})),this.update_placeholder(),this.updateTooltip()}update_placeholder(e){const t=e||this.model.get("placeholder");this.textbox.setAttribute("placeholder",t.toString())}update(e){if(void 0===e||e.updated_view!==this){this.textbox.value=this.model.get("value");let e=this.model.get("rows");null===e&&(e=""),this.textbox.setAttribute("rows",e),this.textbox.disabled=this.model.get("disabled")}return this.updateTabindex(),this.updateTooltip(),super.update()}updateTabindex(){if(!this.textbox)return;const e=this.model.get("tabbable");!0===e?this.textbox.setAttribute("tabIndex","0"):!1===e?this.textbox.setAttribute("tabIndex","-1"):null===e&&this.textbox.removeAttribute("tabIndex")}updateTooltip(){if(!this.textbox)return;const e=this.model.get("tooltip");e?0===this.model.get("description").length&&this.textbox.setAttribute("title",e):this.textbox.removeAttribute("title")}events(){return{"keydown input":"handleKeyDown","keypress input":"handleKeypress","input textarea":"handleChanging","change textarea":"handleChanged"}}handleKeyDown(e){e.stopPropagation()}handleKeypress(e){e.stopPropagation()}handleChanging(e){this.model.get("continuous_update")&&this.handleChanged(e)}handleChanged(e){const t=e.target;this.model.set("value",t.value,{updated_view:this}),this.touch()}handle_message(e){"focus"===e.do?this.textbox.focus():"blur"===e.do&&this.textbox.blur()}}class ps extends is{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"TextView",_model_name:"TextModel",continuous_update:!0})}}class gs extends as{constructor(){super(...arguments),this.inputType="text"}render(){super.render(),this.el.classList.add("widget-text"),this.textbox=document.createElement("input"),this.textbox.setAttribute("type",this.inputType),this.textbox.id=this.label.htmlFor=(0,i.uuid)(),this.textbox.classList.add("widget-input"),this.el.appendChild(this.textbox),this.update(),this.listenTo(this.model,"change:placeholder",((e,t,s)=>{this.update_placeholder(t)})),this.update_placeholder(),this.updateTabindex(),this.updateTooltip()}update_placeholder(e){this.textbox.setAttribute("placeholder",e||this.model.get("placeholder"))}updateTabindex(){if(!this.textbox)return;const e=this.model.get("tabbable");!0===e?this.textbox.setAttribute("tabIndex","0"):!1===e?this.textbox.setAttribute("tabIndex","-1"):null===e&&this.textbox.removeAttribute("tabIndex")}updateTooltip(){if(!this.textbox)return;const e=this.model.get("tooltip");e?0===this.model.get("description").length&&this.textbox.setAttribute("title",e):this.textbox.removeAttribute("title")}update(e){return void 0!==e&&e.updated_view===this||(this.textbox.value!==this.model.get("value")&&(this.textbox.value=this.model.get("value")),this.textbox.disabled=this.model.get("disabled")),super.update()}events(){return{"keydown input":"handleKeyDown","keypress input":"handleKeypress","input input":"handleChanging","change input":"handleChanged"}}handleKeyDown(e){e.stopPropagation()}handleKeypress(e){e.stopPropagation(),13===e.keyCode&&this.send({event:"submit"})}handleChanging(e){this.model.get("continuous_update")&&this.handleChanged(e)}handleChanged(e){const t=e.target;this.model.set("value",t.value,{updated_view:this}),this.touch()}handle_message(e){"focus"===e.do?this.textbox.focus():"blur"===e.do&&this.textbox.blur()}}class ms extends ps{defaults(){return Object.assign(Object.assign({},super.defaults()),{_view_name:"PasswordView",_model_name:"PasswordModel"})}}class _s extends gs{constructor(){super(...arguments),this.inputType="password"}}class bs extends ps{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"ComboboxModel",_view_name:"ComboboxView",options:[],ensure_options:!1})}}class vs extends gs{constructor(){super(...arguments),this.isInitialRender=!0}render(){this.datalist=document.createElement("datalist"),this.datalist.id=(0,i.uuid)(),super.render(),this.textbox.setAttribute("list",this.datalist.id),this.el.appendChild(this.datalist),this.updateTooltip()}update(e){if(super.update(e),!this.datalist)return;const t=this.isValid(this.model.get("value"));if(this.highlightValidState(t),void 0!==e&&e.updated_view||!this.model.hasChanged("options")&&!this.isInitialRender)return;this.isInitialRender=!1;const s=this.model.get("options"),i=document.createDocumentFragment();for(const e of s){const t=document.createElement("option");t.value=e,i.appendChild(t)}this.datalist.appendChild(i)}isValid(e){return!0!==this.model.get("ensure_option")||-1!==this.model.get("options").indexOf(e)}handleChanging(e){const t=e.target,s=this.isValid(t.value);this.highlightValidState(s),s&&super.handleChanging(e)}handleChanged(e){const t=e.target,s=this.isValid(t.value);this.highlightValidState(s),s&&super.handleChanged(e)}handle_message(e){"focus"===e.do?this.textbox.focus():"blur"===e.do&&this.textbox.blur()}highlightValidState(e){this.textbox.classList.toggle("jpwidgets-invalidComboValue",!e)}}class xs extends g{defaults(){return Object.assign(Object.assign({},super.defaults()),{_model_name:"FileUploadModel",_view_name:"FileUploadView",accept:"",description:"Upload",disabled:!1,icon:"upload",button_style:"",multiple:!1,value:[],error:"",style:null})}}xs.serializers=Object.assign(Object.assign({},g.serializers),{value:{serialize:e=>e}});class fs extends i.DOMWidgetView{preinitialize(){this.tagName="button"}render(){super.render(),this.el.classList.add("jupyter-widgets"),this.el.classList.add("widget-upload"),this.el.classList.add("jupyter-button"),this.fileInput=document.createElement("input"),this.fileInput.type="file",this.fileInput.style.display="none",this.el.addEventListener("click",(()=>{this.fileInput.click()})),this.fileInput.addEventListener("click",(()=>{this.fileInput.value=""})),this.fileInput.addEventListener("change",(()=>{var e;const t=[];Array.from(null!==(e=this.fileInput.files)&&void 0!==e?e:[]).forEach((e=>{t.push(new Promise(((t,s)=>{const i=new FileReader;i.onload=()=>{const s=i.result;t({content:s,name:e.name,type:e.type,size:e.size,last_modified:e.lastModified})},i.onerror=()=>{s()},i.onabort=i.onerror,i.readAsArrayBuffer(e)})))})),Promise.all(t).then((e=>{this.model.set({value:e,error:""}),this.touch()})).catch((e=>{console.error("error in file upload: %o",e),this.model.set({error:e}),this.touch()}))})),this.listenTo(this.model,"change:button_style",this.update_button_style),this.set_button_style(),this.update()}update(){this.el.disabled=this.model.get("disabled"),this.el.setAttribute("title",this.model.get("tooltip"));const e=this.model.get("value"),t=`${this.model.get("description")} (${e.length})`,s=this.model.get("icon");if(t.length||s.length){if(this.el.textContent="",s.length){const e=document.createElement("i");e.classList.add("fa"),e.classList.add("fa-"+s),0===t.length&&e.classList.add("center"),this.el.appendChild(e)}this.el.appendChild(document.createTextNode(t))}return this.fileInput.accept=this.model.get("accept"),this.fileInput.multiple=this.model.get("multiple"),super.update()}update_button_style(){this.update_mapped_classes(fs.class_map,"button_style",this.el)}set_button_style(){this.set_mapped_classes(fs.class_map,"button_style",this.el)}}fs.class_map={primary:["mod-primary"],success:["mod-success"],info:["mod-info"],warning:["mod-warning"],danger:["mod-danger"]};const ws=s(7021).i8},7021:e=>{e.exports={i8:"5.0.1"}}}]);
\ No newline at end of file
diff --git a/spaces/mounikakadimi28/ml_salary_prediction/README.md b/spaces/mounikakadimi28/ml_salary_prediction/README.md
deleted file mode 100644
index 2bb446b3d2eaed7acd024fda1f0f84bb0e9b59e3..0000000000000000000000000000000000000000
--- a/spaces/mounikakadimi28/ml_salary_prediction/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Ml Salary Prediction
-emoji: 📚
-colorFrom: purple
-colorTo: green
-sdk: gradio
-sdk_version: 3.47.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/mrm8488/whisper-large-v3/app.py b/spaces/mrm8488/whisper-large-v3/app.py
deleted file mode 100644
index 6871f2ba44806771a554a0335e59ed695311807c..0000000000000000000000000000000000000000
--- a/spaces/mrm8488/whisper-large-v3/app.py
+++ /dev/null
@@ -1,151 +0,0 @@
-import torch
-
-import gradio as gr
-import yt_dlp as youtube_dl
-from transformers import pipeline
-from transformers.pipelines.audio_utils import ffmpeg_read
-
-import tempfile
-import os
-
-MODEL_NAME = "openai/whisper-large-v3"
-BATCH_SIZE = 8
-FILE_LIMIT_MB = 1000
-YT_LENGTH_LIMIT_S = 3600 # limit to 1 hour YouTube files
-
-device = 0 if torch.cuda.is_available() else "cpu"
-
-pipe = pipeline(
- task="automatic-speech-recognition",
- model=MODEL_NAME,
- chunk_length_s=30,
- device=device,
-)
-
-
-def transcribe(inputs, task):
- if inputs is None:
- raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
-
- text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
- return text
-
-
-def _return_yt_html_embed(yt_url):
- video_id = yt_url.split("?v=")[-1]
- HTML_str = (
- f'
-Construido sobre Tortoise, XTTS ha sufrido cambios importantes en el modelo que facilitan la clonación de voz entre idiomas y la generación de voz multilingüe.
-
-Este es el mismo modelo que alimenta Coqui Studio y Coqui API, sin embargo, aplicamos algunos trucos para hacerlo más rápido y soportar inferencia en streaming.
-
-
-"""
-
-
-article = """
-
This UI to the model was assembled by @multimodalartBiases acknowledgment
Who owns the images produced by this demo?
-Hanthana Kathawa: A Classic Sri Lankan Love Story
-Hanthana Kathawa Novel Download Pdfl
-
-
-
\ No newline at end of file
diff --git a/spaces/nikitaPDL2023/assignment4/detectron2/detectron2/layers/deform_conv.py b/spaces/nikitaPDL2023/assignment4/detectron2/detectron2/layers/deform_conv.py
deleted file mode 100644
index dffb720c2a8d10d9273752dbdd291a3714f91338..0000000000000000000000000000000000000000
--- a/spaces/nikitaPDL2023/assignment4/detectron2/detectron2/layers/deform_conv.py
+++ /dev/null
@@ -1,514 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import math
-from functools import lru_cache
-import torch
-from torch import nn
-from torch.autograd import Function
-from torch.autograd.function import once_differentiable
-from torch.nn.modules.utils import _pair
-from torchvision.ops import deform_conv2d
-
-from detectron2.utils.develop import create_dummy_class, create_dummy_func
-
-from .wrappers import _NewEmptyTensorOp
-
-
-class _DeformConv(Function):
- @staticmethod
- def forward(
- ctx,
- input,
- offset,
- weight,
- stride=1,
- padding=0,
- dilation=1,
- groups=1,
- deformable_groups=1,
- im2col_step=64,
- ):
- if input is not None and input.dim() != 4:
- raise ValueError(
- "Expected 4D tensor as input, got {}D tensor instead.".format(input.dim())
- )
- ctx.stride = _pair(stride)
- ctx.padding = _pair(padding)
- ctx.dilation = _pair(dilation)
- ctx.groups = groups
- ctx.deformable_groups = deformable_groups
- ctx.im2col_step = im2col_step
-
- ctx.save_for_backward(input, offset, weight)
-
- output = input.new_empty(
- _DeformConv._output_size(input, weight, ctx.padding, ctx.dilation, ctx.stride)
- )
-
- ctx.bufs_ = [input.new_empty(0), input.new_empty(0)] # columns, ones
-
- if not input.is_cuda:
- # TODO: let torchvision support full features of our deformconv.
- if deformable_groups != 1:
- raise NotImplementedError(
- "Deformable Conv with deformable_groups != 1 is not supported on CPUs!"
- )
- return deform_conv2d(
- input, offset, weight, stride=stride, padding=padding, dilation=dilation
- )
- else:
- cur_im2col_step = _DeformConv._cal_im2col_step(input.shape[0], ctx.im2col_step)
- assert (input.shape[0] % cur_im2col_step) == 0, "im2col step must divide batchsize"
-
- _C.deform_conv_forward(
- input,
- weight,
- offset,
- output,
- ctx.bufs_[0],
- ctx.bufs_[1],
- weight.size(3),
- weight.size(2),
- ctx.stride[1],
- ctx.stride[0],
- ctx.padding[1],
- ctx.padding[0],
- ctx.dilation[1],
- ctx.dilation[0],
- ctx.groups,
- ctx.deformable_groups,
- cur_im2col_step,
- )
- return output
-
- @staticmethod
- @once_differentiable
- def backward(ctx, grad_output):
- input, offset, weight = ctx.saved_tensors
-
- grad_input = grad_offset = grad_weight = None
-
- if not grad_output.is_cuda:
- raise NotImplementedError("Deformable Conv is not supported on CPUs!")
- else:
- cur_im2col_step = _DeformConv._cal_im2col_step(input.shape[0], ctx.im2col_step)
- assert (input.shape[0] % cur_im2col_step) == 0, "im2col step must divide batchsize"
-
- if ctx.needs_input_grad[0] or ctx.needs_input_grad[1]:
- grad_input = torch.zeros_like(input)
- grad_offset = torch.zeros_like(offset)
- _C.deform_conv_backward_input(
- input,
- offset,
- grad_output,
- grad_input,
- grad_offset,
- weight,
- ctx.bufs_[0],
- weight.size(3),
- weight.size(2),
- ctx.stride[1],
- ctx.stride[0],
- ctx.padding[1],
- ctx.padding[0],
- ctx.dilation[1],
- ctx.dilation[0],
- ctx.groups,
- ctx.deformable_groups,
- cur_im2col_step,
- )
-
- if ctx.needs_input_grad[2]:
- grad_weight = torch.zeros_like(weight)
- _C.deform_conv_backward_filter(
- input,
- offset,
- grad_output,
- grad_weight,
- ctx.bufs_[0],
- ctx.bufs_[1],
- weight.size(3),
- weight.size(2),
- ctx.stride[1],
- ctx.stride[0],
- ctx.padding[1],
- ctx.padding[0],
- ctx.dilation[1],
- ctx.dilation[0],
- ctx.groups,
- ctx.deformable_groups,
- 1,
- cur_im2col_step,
- )
-
- return grad_input, grad_offset, grad_weight, None, None, None, None, None, None
-
- @staticmethod
- def _output_size(input, weight, padding, dilation, stride):
- channels = weight.size(0)
- output_size = (input.size(0), channels)
- for d in range(input.dim() - 2):
- in_size = input.size(d + 2)
- pad = padding[d]
- kernel = dilation[d] * (weight.size(d + 2) - 1) + 1
- stride_ = stride[d]
- output_size += ((in_size + (2 * pad) - kernel) // stride_ + 1,)
- if not all(map(lambda s: s > 0, output_size)):
- raise ValueError(
- "convolution input is too small (output would be {})".format(
- "x".join(map(str, output_size))
- )
- )
- return output_size
-
- @staticmethod
- @lru_cache(maxsize=128)
- def _cal_im2col_step(input_size, default_size):
- """
- Calculate proper im2col step size, which should be divisible by input_size and not larger
- than prefer_size. Meanwhile the step size should be as large as possible to be more
- efficient. So we choose the largest one among all divisors of input_size which are smaller
- than prefer_size.
- :param input_size: input batch size .
- :param default_size: default preferred im2col step size.
- :return: the largest proper step size.
- """
- if input_size <= default_size:
- return input_size
- best_step = 1
- for step in range(2, min(int(math.sqrt(input_size)) + 1, default_size)):
- if input_size % step == 0:
- if input_size // step <= default_size:
- return input_size // step
- best_step = step
-
- return best_step
-
-
-class _ModulatedDeformConv(Function):
- @staticmethod
- def forward(
- ctx,
- input,
- offset,
- mask,
- weight,
- bias=None,
- stride=1,
- padding=0,
- dilation=1,
- groups=1,
- deformable_groups=1,
- ):
- ctx.stride = stride
- ctx.padding = padding
- ctx.dilation = dilation
- ctx.groups = groups
- ctx.deformable_groups = deformable_groups
- ctx.with_bias = bias is not None
- if not ctx.with_bias:
- bias = input.new_empty(1) # fake tensor
- if not input.is_cuda:
- raise NotImplementedError("Deformable Conv is not supported on CPUs!")
- if (
- weight.requires_grad
- or mask.requires_grad
- or offset.requires_grad
- or input.requires_grad
- ):
- ctx.save_for_backward(input, offset, mask, weight, bias)
- output = input.new_empty(_ModulatedDeformConv._infer_shape(ctx, input, weight))
- ctx._bufs = [input.new_empty(0), input.new_empty(0)]
- _C.modulated_deform_conv_forward(
- input,
- weight,
- bias,
- ctx._bufs[0],
- offset,
- mask,
- output,
- ctx._bufs[1],
- weight.shape[2],
- weight.shape[3],
- ctx.stride,
- ctx.stride,
- ctx.padding,
- ctx.padding,
- ctx.dilation,
- ctx.dilation,
- ctx.groups,
- ctx.deformable_groups,
- ctx.with_bias,
- )
- return output
-
- @staticmethod
- @once_differentiable
- def backward(ctx, grad_output):
- if not grad_output.is_cuda:
- raise NotImplementedError("Deformable Conv is not supported on CPUs!")
- input, offset, mask, weight, bias = ctx.saved_tensors
- grad_input = torch.zeros_like(input)
- grad_offset = torch.zeros_like(offset)
- grad_mask = torch.zeros_like(mask)
- grad_weight = torch.zeros_like(weight)
- grad_bias = torch.zeros_like(bias)
- _C.modulated_deform_conv_backward(
- input,
- weight,
- bias,
- ctx._bufs[0],
- offset,
- mask,
- ctx._bufs[1],
- grad_input,
- grad_weight,
- grad_bias,
- grad_offset,
- grad_mask,
- grad_output,
- weight.shape[2],
- weight.shape[3],
- ctx.stride,
- ctx.stride,
- ctx.padding,
- ctx.padding,
- ctx.dilation,
- ctx.dilation,
- ctx.groups,
- ctx.deformable_groups,
- ctx.with_bias,
- )
- if not ctx.with_bias:
- grad_bias = None
-
- return (
- grad_input,
- grad_offset,
- grad_mask,
- grad_weight,
- grad_bias,
- None,
- None,
- None,
- None,
- None,
- )
-
- @staticmethod
- def _infer_shape(ctx, input, weight):
- n = input.size(0)
- channels_out = weight.size(0)
- height, width = input.shape[2:4]
- kernel_h, kernel_w = weight.shape[2:4]
- height_out = (
- height + 2 * ctx.padding - (ctx.dilation * (kernel_h - 1) + 1)
- ) // ctx.stride + 1
- width_out = (
- width + 2 * ctx.padding - (ctx.dilation * (kernel_w - 1) + 1)
- ) // ctx.stride + 1
- return n, channels_out, height_out, width_out
-
-
-deform_conv = _DeformConv.apply
-modulated_deform_conv = _ModulatedDeformConv.apply
-
-
-class DeformConv(nn.Module):
- def __init__(
- self,
- in_channels,
- out_channels,
- kernel_size,
- stride=1,
- padding=0,
- dilation=1,
- groups=1,
- deformable_groups=1,
- bias=False,
- norm=None,
- activation=None,
- ):
- """
- Deformable convolution from :paper:`deformconv`.
-
- Arguments are similar to :class:`Conv2D`. Extra arguments:
-
- Args:
- deformable_groups (int): number of groups used in deformable convolution.
- norm (nn.Module, optional): a normalization layer
- activation (callable(Tensor) -> Tensor): a callable activation function
- """
- super(DeformConv, self).__init__()
-
- assert not bias
- assert in_channels % groups == 0, "in_channels {} cannot be divisible by groups {}".format(
- in_channels, groups
- )
- assert (
- out_channels % groups == 0
- ), "out_channels {} cannot be divisible by groups {}".format(out_channels, groups)
-
- self.in_channels = in_channels
- self.out_channels = out_channels
- self.kernel_size = _pair(kernel_size)
- self.stride = _pair(stride)
- self.padding = _pair(padding)
- self.dilation = _pair(dilation)
- self.groups = groups
- self.deformable_groups = deformable_groups
- self.norm = norm
- self.activation = activation
-
- self.weight = nn.Parameter(
- torch.Tensor(out_channels, in_channels // self.groups, *self.kernel_size)
- )
- self.bias = None
-
- nn.init.kaiming_uniform_(self.weight, nonlinearity="relu")
-
- def forward(self, x, offset):
- if x.numel() == 0:
- # When input is empty, we want to return a empty tensor with "correct" shape,
- # So that the following operations will not panic
- # if they check for the shape of the tensor.
- # This computes the height and width of the output tensor
- output_shape = [
- (i + 2 * p - (di * (k - 1) + 1)) // s + 1
- for i, p, di, k, s in zip(
- x.shape[-2:], self.padding, self.dilation, self.kernel_size, self.stride
- )
- ]
- output_shape = [x.shape[0], self.weight.shape[0]] + output_shape
- return _NewEmptyTensorOp.apply(x, output_shape)
-
- x = deform_conv(
- x,
- offset,
- self.weight,
- self.stride,
- self.padding,
- self.dilation,
- self.groups,
- self.deformable_groups,
- )
- if self.norm is not None:
- x = self.norm(x)
- if self.activation is not None:
- x = self.activation(x)
- return x
-
- def extra_repr(self):
- tmpstr = "in_channels=" + str(self.in_channels)
- tmpstr += ", out_channels=" + str(self.out_channels)
- tmpstr += ", kernel_size=" + str(self.kernel_size)
- tmpstr += ", stride=" + str(self.stride)
- tmpstr += ", padding=" + str(self.padding)
- tmpstr += ", dilation=" + str(self.dilation)
- tmpstr += ", groups=" + str(self.groups)
- tmpstr += ", deformable_groups=" + str(self.deformable_groups)
- tmpstr += ", bias=False"
- return tmpstr
-
-
-class ModulatedDeformConv(nn.Module):
- def __init__(
- self,
- in_channels,
- out_channels,
- kernel_size,
- stride=1,
- padding=0,
- dilation=1,
- groups=1,
- deformable_groups=1,
- bias=True,
- norm=None,
- activation=None,
- ):
- """
- Modulated deformable convolution from :paper:`deformconv2`.
-
- Arguments are similar to :class:`Conv2D`. Extra arguments:
-
- Args:
- deformable_groups (int): number of groups used in deformable convolution.
- norm (nn.Module, optional): a normalization layer
- activation (callable(Tensor) -> Tensor): a callable activation function
- """
- super(ModulatedDeformConv, self).__init__()
- self.in_channels = in_channels
- self.out_channels = out_channels
- self.kernel_size = _pair(kernel_size)
- self.stride = stride
- self.padding = padding
- self.dilation = dilation
- self.groups = groups
- self.deformable_groups = deformable_groups
- self.with_bias = bias
- self.norm = norm
- self.activation = activation
-
- self.weight = nn.Parameter(
- torch.Tensor(out_channels, in_channels // groups, *self.kernel_size)
- )
- if bias:
- self.bias = nn.Parameter(torch.Tensor(out_channels))
- else:
- self.bias = None
-
- nn.init.kaiming_uniform_(self.weight, nonlinearity="relu")
- if self.bias is not None:
- nn.init.constant_(self.bias, 0)
-
- def forward(self, x, offset, mask):
- if x.numel() == 0:
- output_shape = [
- (i + 2 * p - (di * (k - 1) + 1)) // s + 1
- for i, p, di, k, s in zip(
- x.shape[-2:], self.padding, self.dilation, self.kernel_size, self.stride
- )
- ]
- output_shape = [x.shape[0], self.weight.shape[0]] + output_shape
- return _NewEmptyTensorOp.apply(x, output_shape)
-
- x = modulated_deform_conv(
- x,
- offset,
- mask,
- self.weight,
- self.bias,
- self.stride,
- self.padding,
- self.dilation,
- self.groups,
- self.deformable_groups,
- )
- if self.norm is not None:
- x = self.norm(x)
- if self.activation is not None:
- x = self.activation(x)
- return x
-
- def extra_repr(self):
- tmpstr = "in_channels=" + str(self.in_channels)
- tmpstr += ", out_channels=" + str(self.out_channels)
- tmpstr += ", kernel_size=" + str(self.kernel_size)
- tmpstr += ", stride=" + str(self.stride)
- tmpstr += ", padding=" + str(self.padding)
- tmpstr += ", dilation=" + str(self.dilation)
- tmpstr += ", groups=" + str(self.groups)
- tmpstr += ", deformable_groups=" + str(self.deformable_groups)
- tmpstr += ", bias=" + str(self.with_bias)
- return tmpstr
-
-
-try:
- from detectron2 import _C
-except ImportError:
- # TODO: register ops natively so there is no need to import _C.
- _msg = "detectron2 is not compiled successfully, please build following the instructions!"
- _args = ("detectron2._C", _msg)
- DeformConv = create_dummy_class("DeformConv", *_args)
- ModulatedDeformConv = create_dummy_class("ModulatedDeformConv", *_args)
- deform_conv = create_dummy_func("deform_conv", *_args)
- modulated_deform_conv = create_dummy_func("modulated_deform_conv", *_args)
diff --git a/spaces/nontGcob/T2E_Vocabulary_Exam_Generator/README.md b/spaces/nontGcob/T2E_Vocabulary_Exam_Generator/README.md
deleted file mode 100644
index 203a47e4f0f533cca256248d98b87522d02364e2..0000000000000000000000000000000000000000
--- a/spaces/nontGcob/T2E_Vocabulary_Exam_Generator/README.md
+++ /dev/null
@@ -1,63 +0,0 @@
----
-title: T2E Vocabulary Exam Generator
-emoji: ✏️
-colorFrom: blue
-colorTo: blue
-sdk: gradio
-sdk_version: 2.9.1
-python_version: 3.10.4
-app_file: app.py
-models: [osanseviero/BigGAN-deep-128, t5-small]
-datasets: [emotion]
-license: mit
-pinned: true
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
-
-# T2E Vocabulary Exam Generator
-T2E Vocabulary Exam Generator as the name suggest, is an open souce program that allows user, in this case being teachers, to generate English vocabulary exam right from their browser. We aim to help reduce the pain point of teacher having to spend his/her/their precious time and effort to make the entire vocabulary exam or quiz. To try it out, click the Demo link in the Quick Links section below.
-
-This readme.md file is an explanation of this folder that it's in.
-
-## Quick Links
-- Demo: https://huggingface.co/spaces/nontGcob/T2E_Vocabulary_Exam_Generator
-- Documentation: https://mario-world.medium.com/text-to-exam-generator-nlp-using-machine-learning-71da8dd93a4a
-
-## Important File Explanation
-- Exploratory_Data_Analysis.ipynb
- - This code runs through the entire dataset that we have and analyse the part of speech of all the lexical vocabulary, the max/min/average vocabulary length, and the number of times a word is presented
-- Test_&_Fine_tune_&_Retest.ipynb
- - This code tests the accuracy of the pre-trained model which is our baseline. It fine-tunes the model. And then, it tests the fine-tuned model again to check whether the accuracy has increased or not.
-- Error_Analysis.ipynb
- - This code analyses the prediction by analysing the type number of correct and wrong vocabulary predictions, the types of the part of speech of the correct and wrong vocab predictions, and the average vocabulary length of the correct and wrong vocab predictions.
-
-## Note
-Please keep in mind that in order to run the .ipynb file in this folder, you must also download the "simple_trained_wsd_pipeline" and "semcor_samples_4-samples.json" as well which are not included in the folder due to the file size limitation of the code that can be uploaded to GitHub. For more information and the explanation of the entire process of this machine learning project, visit the Documentation link that is attached above in the Quick Links section.
-
-## Contact me
-- Name: Nutnornont Chamadol
-- Email: nontc49@gmail.com
-- Visit my personal website https://nontgcob.com/ to learn more about me.
-
-## The MIT License (MIT)
-
-Copyright (c) 2023 Nutnornont Chamadol
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
\ No newline at end of file
diff --git a/spaces/odettecantswim/vits-models-genshin/text/cleaners.py b/spaces/odettecantswim/vits-models-genshin/text/cleaners.py
deleted file mode 100644
index 263df9c0f7c185290600454abfff464e7f774576..0000000000000000000000000000000000000000
--- a/spaces/odettecantswim/vits-models-genshin/text/cleaners.py
+++ /dev/null
@@ -1,134 +0,0 @@
-import re
-from text.japanese import japanese_to_romaji_with_accent, japanese_to_ipa, japanese_to_ipa2, japanese_to_ipa3
-from text.korean import latin_to_hangul, number_to_hangul, divide_hangul, korean_to_lazy_ipa, korean_to_ipa
-from text.mandarin import number_to_chinese, chinese_to_bopomofo, latin_to_bopomofo, chinese_to_romaji, chinese_to_lazy_ipa, chinese_to_ipa, chinese_to_ipa2
-from text.sanskrit import devanagari_to_ipa
-from text.english import english_to_lazy_ipa, english_to_ipa2, english_to_lazy_ipa2
-from text.thai import num_to_thai, latin_to_thai
-# from text.shanghainese import shanghainese_to_ipa
-# from text.cantonese import cantonese_to_ipa
-# from text.ngu_dialect import ngu_dialect_to_ipa
-
-
-def japanese_cleaners(text):
- text = japanese_to_romaji_with_accent(text)
- text = re.sub(r'([A-Za-z])$', r'\1.', text)
- return text
-
-
-def japanese_cleaners2(text):
- return japanese_cleaners(text).replace('ts', 'ʦ').replace('...', '…')
-
-
-def korean_cleaners(text):
- '''Pipeline for Korean text'''
- text = latin_to_hangul(text)
- text = number_to_hangul(text)
- text = divide_hangul(text)
- text = re.sub(r'([\u3131-\u3163])$', r'\1.', text)
- return text
-
-
-# def chinese_cleaners(text):
-# '''Pipeline for Chinese text'''
-# text = number_to_chinese(text)
-# text = chinese_to_bopomofo(text)
-# text = latin_to_bopomofo(text)
-# text = re.sub(r'([ˉˊˇˋ˙])$', r'\1。', text)
-# return text
-
-def chinese_cleaners(text):
- from pypinyin import Style, pinyin
- text = text.replace("[ZH]", "")
- phones = [phone[0] for phone in pinyin(text, style=Style.TONE3)]
- return ' '.join(phones)
-
-
-def zh_ja_mixture_cleaners(text):
- text = re.sub(r'\[ZH\](.*?)\[ZH\]',
- lambda x: chinese_to_romaji(x.group(1))+' ', text)
- text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: japanese_to_romaji_with_accent(
- x.group(1)).replace('ts', 'ʦ').replace('u', 'ɯ').replace('...', '…')+' ', text)
- text = re.sub(r'\s+$', '', text)
- text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
- return text
-
-
-def sanskrit_cleaners(text):
- text = text.replace('॥', '।').replace('ॐ', 'ओम्')
- text = re.sub(r'([^।])$', r'\1।', text)
- return text
-
-
-def cjks_cleaners(text):
- text = re.sub(r'\[ZH\](.*?)\[ZH\]',
- lambda x: chinese_to_lazy_ipa(x.group(1))+' ', text)
- text = re.sub(r'\[JA\](.*?)\[JA\]',
- lambda x: japanese_to_ipa(x.group(1))+' ', text)
- text = re.sub(r'\[KO\](.*?)\[KO\]',
- lambda x: korean_to_lazy_ipa(x.group(1))+' ', text)
- text = re.sub(r'\[SA\](.*?)\[SA\]',
- lambda x: devanagari_to_ipa(x.group(1))+' ', text)
- text = re.sub(r'\[EN\](.*?)\[EN\]',
- lambda x: english_to_lazy_ipa(x.group(1))+' ', text)
- text = re.sub(r'\s+$', '', text)
- text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
- return text
-
-
-def cjke_cleaners(text):
- text = re.sub(r'\[ZH\](.*?)\[ZH\]', lambda x: chinese_to_lazy_ipa(x.group(1)).replace(
- 'ʧ', 'tʃ').replace('ʦ', 'ts').replace('ɥan', 'ɥæn')+' ', text)
- text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: japanese_to_ipa(x.group(1)).replace('ʧ', 'tʃ').replace(
- 'ʦ', 'ts').replace('ɥan', 'ɥæn').replace('ʥ', 'dz')+' ', text)
- text = re.sub(r'\[KO\](.*?)\[KO\]',
- lambda x: korean_to_ipa(x.group(1))+' ', text)
- text = re.sub(r'\[EN\](.*?)\[EN\]', lambda x: english_to_ipa2(x.group(1)).replace('ɑ', 'a').replace(
- 'ɔ', 'o').replace('ɛ', 'e').replace('ɪ', 'i').replace('ʊ', 'u')+' ', text)
- text = re.sub(r'\s+$', '', text)
- text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
- return text
-
-
-def cjke_cleaners2(text):
- text = re.sub(r'\[ZH\](.*?)\[ZH\]',
- lambda x: chinese_to_ipa(x.group(1))+' ', text)
- text = re.sub(r'\[JA\](.*?)\[JA\]',
- lambda x: japanese_to_ipa2(x.group(1))+' ', text)
- text = re.sub(r'\[KO\](.*?)\[KO\]',
- lambda x: korean_to_ipa(x.group(1))+' ', text)
- text = re.sub(r'\[EN\](.*?)\[EN\]',
- lambda x: english_to_ipa2(x.group(1))+' ', text)
- text = re.sub(r'\s+$', '', text)
- text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
- return text
-
-
-def thai_cleaners(text):
- text = num_to_thai(text)
- text = latin_to_thai(text)
- return text
-
-
-# def shanghainese_cleaners(text):
-# text = shanghainese_to_ipa(text)
-# text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-# return text
-
-
-# def chinese_dialect_cleaners(text):
-# text = re.sub(r'\[ZH\](.*?)\[ZH\]',
-# lambda x: chinese_to_ipa2(x.group(1))+' ', text)
-# text = re.sub(r'\[JA\](.*?)\[JA\]',
-# lambda x: japanese_to_ipa3(x.group(1)).replace('Q', 'ʔ')+' ', text)
-# text = re.sub(r'\[SH\](.*?)\[SH\]', lambda x: shanghainese_to_ipa(x.group(1)).replace('1', '˥˧').replace('5',
-# '˧˧˦').replace('6', '˩˩˧').replace('7', '˥').replace('8', '˩˨').replace('ᴀ', 'ɐ').replace('ᴇ', 'e')+' ', text)
-# text = re.sub(r'\[GD\](.*?)\[GD\]',
-# lambda x: cantonese_to_ipa(x.group(1))+' ', text)
-# text = re.sub(r'\[EN\](.*?)\[EN\]',
-# lambda x: english_to_lazy_ipa2(x.group(1))+' ', text)
-# text = re.sub(r'\[([A-Z]{2})\](.*?)\[\1\]', lambda x: ngu_dialect_to_ipa(x.group(2), x.group(
-# 1)).replace('ʣ', 'dz').replace('ʥ', 'dʑ').replace('ʦ', 'ts').replace('ʨ', 'tɕ')+' ', text)
-# text = re.sub(r'\s+$', '', text)
-# text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-# return text
diff --git a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/schedulers/heun.md b/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/schedulers/heun.md
deleted file mode 100644
index 725c1a67f4370ea0825923fed997c86e613c3788..0000000000000000000000000000000000000000
--- a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/schedulers/heun.md
+++ /dev/null
@@ -1,21 +0,0 @@
-
-
-# HeunDiscreteScheduler
-
-The Heun scheduler (Algorithm 1) is from the [Elucidating the Design Space of Diffusion-Based Generative Models](https://huggingface.co/papers/2206.00364) paper by Karras et al. The scheduler is ported from the [k-diffusion](https://github.com/crowsonkb/k-diffusion) library and created by [Katherine Crowson](https://github.com/crowsonkb/).
-
-## HeunDiscreteScheduler
-[[autodoc]] HeunDiscreteScheduler
-
-## SchedulerOutput
-[[autodoc]] schedulers.scheduling_utils.SchedulerOutput
\ No newline at end of file
diff --git a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/scripts/convert_stable_diffusion_controlnet_to_onnx.py b/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/scripts/convert_stable_diffusion_controlnet_to_onnx.py
deleted file mode 100644
index 4af39b28783681c9e6626cd2c003f2b8635224a5..0000000000000000000000000000000000000000
--- a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/scripts/convert_stable_diffusion_controlnet_to_onnx.py
+++ /dev/null
@@ -1,505 +0,0 @@
-import argparse
-import os
-import shutil
-from pathlib import Path
-
-import onnx
-import onnx_graphsurgeon as gs
-import torch
-from onnx import shape_inference
-from packaging import version
-from polygraphy.backend.onnx.loader import fold_constants
-from torch.onnx import export
-
-from diffusers import (
- ControlNetModel,
- StableDiffusionControlNetImg2ImgPipeline,
-)
-from diffusers.models.attention_processor import AttnProcessor
-from diffusers.pipelines.controlnet.pipeline_controlnet_sd_xl import StableDiffusionXLControlNetPipeline
-
-
-is_torch_less_than_1_11 = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
-is_torch_2_0_1 = version.parse(version.parse(torch.__version__).base_version) == version.parse("2.0.1")
-
-
-class Optimizer:
- def __init__(self, onnx_graph, verbose=False):
- self.graph = gs.import_onnx(onnx_graph)
- self.verbose = verbose
-
- def info(self, prefix):
- if self.verbose:
- print(
- f"{prefix} .. {len(self.graph.nodes)} nodes, {len(self.graph.tensors().keys())} tensors, {len(self.graph.inputs)} inputs, {len(self.graph.outputs)} outputs"
- )
-
- def cleanup(self, return_onnx=False):
- self.graph.cleanup().toposort()
- if return_onnx:
- return gs.export_onnx(self.graph)
-
- def select_outputs(self, keep, names=None):
- self.graph.outputs = [self.graph.outputs[o] for o in keep]
- if names:
- for i, name in enumerate(names):
- self.graph.outputs[i].name = name
-
- def fold_constants(self, return_onnx=False):
- onnx_graph = fold_constants(gs.export_onnx(self.graph), allow_onnxruntime_shape_inference=True)
- self.graph = gs.import_onnx(onnx_graph)
- if return_onnx:
- return onnx_graph
-
- def infer_shapes(self, return_onnx=False):
- onnx_graph = gs.export_onnx(self.graph)
- if onnx_graph.ByteSize() > 2147483648:
- raise TypeError("ERROR: model size exceeds supported 2GB limit")
- else:
- onnx_graph = shape_inference.infer_shapes(onnx_graph)
-
- self.graph = gs.import_onnx(onnx_graph)
- if return_onnx:
- return onnx_graph
-
-
-def optimize(onnx_graph, name, verbose):
- opt = Optimizer(onnx_graph, verbose=verbose)
- opt.info(name + ": original")
- opt.cleanup()
- opt.info(name + ": cleanup")
- opt.fold_constants()
- opt.info(name + ": fold constants")
- # opt.infer_shapes()
- # opt.info(name + ': shape inference')
- onnx_opt_graph = opt.cleanup(return_onnx=True)
- opt.info(name + ": finished")
- return onnx_opt_graph
-
-
-class UNet2DConditionControlNetModel(torch.nn.Module):
- def __init__(
- self,
- unet,
- controlnets: ControlNetModel,
- ):
- super().__init__()
- self.unet = unet
- self.controlnets = controlnets
-
- def forward(
- self,
- sample,
- timestep,
- encoder_hidden_states,
- controlnet_conds,
- controlnet_scales,
- ):
- for i, (controlnet_cond, conditioning_scale, controlnet) in enumerate(
- zip(controlnet_conds, controlnet_scales, self.controlnets)
- ):
- down_samples, mid_sample = controlnet(
- sample,
- timestep,
- encoder_hidden_states=encoder_hidden_states,
- controlnet_cond=controlnet_cond,
- conditioning_scale=conditioning_scale,
- return_dict=False,
- )
-
- # merge samples
- if i == 0:
- down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
- else:
- down_block_res_samples = [
- samples_prev + samples_curr
- for samples_prev, samples_curr in zip(down_block_res_samples, down_samples)
- ]
- mid_block_res_sample += mid_sample
-
- noise_pred = self.unet(
- sample,
- timestep,
- encoder_hidden_states=encoder_hidden_states,
- down_block_additional_residuals=down_block_res_samples,
- mid_block_additional_residual=mid_block_res_sample,
- return_dict=False,
- )[0]
- return noise_pred
-
-
-class UNet2DConditionXLControlNetModel(torch.nn.Module):
- def __init__(
- self,
- unet,
- controlnets: ControlNetModel,
- ):
- super().__init__()
- self.unet = unet
- self.controlnets = controlnets
-
- def forward(
- self,
- sample,
- timestep,
- encoder_hidden_states,
- controlnet_conds,
- controlnet_scales,
- text_embeds,
- time_ids,
- ):
- added_cond_kwargs = {"text_embeds": text_embeds, "time_ids": time_ids}
- for i, (controlnet_cond, conditioning_scale, controlnet) in enumerate(
- zip(controlnet_conds, controlnet_scales, self.controlnets)
- ):
- down_samples, mid_sample = controlnet(
- sample,
- timestep,
- encoder_hidden_states=encoder_hidden_states,
- controlnet_cond=controlnet_cond,
- conditioning_scale=conditioning_scale,
- added_cond_kwargs=added_cond_kwargs,
- return_dict=False,
- )
-
- # merge samples
- if i == 0:
- down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
- else:
- down_block_res_samples = [
- samples_prev + samples_curr
- for samples_prev, samples_curr in zip(down_block_res_samples, down_samples)
- ]
- mid_block_res_sample += mid_sample
-
- noise_pred = self.unet(
- sample,
- timestep,
- encoder_hidden_states=encoder_hidden_states,
- down_block_additional_residuals=down_block_res_samples,
- mid_block_additional_residual=mid_block_res_sample,
- added_cond_kwargs=added_cond_kwargs,
- return_dict=False,
- )[0]
- return noise_pred
-
-
-def onnx_export(
- model,
- model_args: tuple,
- output_path: Path,
- ordered_input_names,
- output_names,
- dynamic_axes,
- opset,
- use_external_data_format=False,
-):
- output_path.parent.mkdir(parents=True, exist_ok=True)
- # PyTorch deprecated the `enable_onnx_checker` and `use_external_data_format` arguments in v1.11,
- # so we check the torch version for backwards compatibility
- with torch.inference_mode(), torch.autocast("cuda"):
- if is_torch_less_than_1_11:
- export(
- model,
- model_args,
- f=output_path.as_posix(),
- input_names=ordered_input_names,
- output_names=output_names,
- dynamic_axes=dynamic_axes,
- do_constant_folding=True,
- use_external_data_format=use_external_data_format,
- enable_onnx_checker=True,
- opset_version=opset,
- )
- else:
- export(
- model,
- model_args,
- f=output_path.as_posix(),
- input_names=ordered_input_names,
- output_names=output_names,
- dynamic_axes=dynamic_axes,
- do_constant_folding=True,
- opset_version=opset,
- )
-
-
-@torch.no_grad()
-def convert_models(
- model_path: str, controlnet_path: list, output_path: str, opset: int, fp16: bool = False, sd_xl: bool = False
-):
- """
- Function to convert models in stable diffusion controlnet pipeline into ONNX format
-
- Example:
- python convert_stable_diffusion_controlnet_to_onnx.py
- --model_path danbrown/RevAnimated-v1-2-2
- --controlnet_path lllyasviel/control_v11f1e_sd15_tile ioclab/brightness-controlnet
- --output_path path-to-models-stable_diffusion/RevAnimated-v1-2-2
- --fp16
-
- Example for SD XL:
- python convert_stable_diffusion_controlnet_to_onnx.py
- --model_path stabilityai/stable-diffusion-xl-base-1.0
- --controlnet_path SargeZT/sdxl-controlnet-seg
- --output_path path-to-models-stable_diffusion/stable-diffusion-xl-base-1.0
- --fp16
- --sd_xl
-
- Returns:
- create 4 onnx models in output path
- text_encoder/model.onnx
- unet/model.onnx + unet/weights.pb
- vae_encoder/model.onnx
- vae_decoder/model.onnx
-
- run test script in diffusers/examples/community
- python test_onnx_controlnet.py
- --sd_model danbrown/RevAnimated-v1-2-2
- --onnx_model_dir path-to-models-stable_diffusion/RevAnimated-v1-2-2
- --qr_img_path path-to-qr-code-image
- """
- dtype = torch.float16 if fp16 else torch.float32
- if fp16 and torch.cuda.is_available():
- device = "cuda"
- elif fp16 and not torch.cuda.is_available():
- raise ValueError("`float16` model export is only supported on GPUs with CUDA")
- else:
- device = "cpu"
-
- # init controlnet
- controlnets = []
- for path in controlnet_path:
- controlnet = ControlNetModel.from_pretrained(path, torch_dtype=dtype).to(device)
- if is_torch_2_0_1:
- controlnet.set_attn_processor(AttnProcessor())
- controlnets.append(controlnet)
-
- if sd_xl:
- if len(controlnets) == 1:
- controlnet = controlnets[0]
- else:
- raise ValueError("MultiControlNet is not yet supported.")
- pipeline = StableDiffusionXLControlNetPipeline.from_pretrained(
- model_path, controlnet=controlnet, torch_dtype=dtype, variant="fp16", use_safetensors=True
- ).to(device)
- else:
- pipeline = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
- model_path, controlnet=controlnets, torch_dtype=dtype
- ).to(device)
-
- output_path = Path(output_path)
- if is_torch_2_0_1:
- pipeline.unet.set_attn_processor(AttnProcessor())
- pipeline.vae.set_attn_processor(AttnProcessor())
-
- # # TEXT ENCODER
- num_tokens = pipeline.text_encoder.config.max_position_embeddings
- text_hidden_size = pipeline.text_encoder.config.hidden_size
- text_input = pipeline.tokenizer(
- "A sample prompt",
- padding="max_length",
- max_length=pipeline.tokenizer.model_max_length,
- truncation=True,
- return_tensors="pt",
- )
- onnx_export(
- pipeline.text_encoder,
- # casting to torch.int32 until the CLIP fix is released: https://github.com/huggingface/transformers/pull/18515/files
- model_args=(text_input.input_ids.to(device=device, dtype=torch.int32)),
- output_path=output_path / "text_encoder" / "model.onnx",
- ordered_input_names=["input_ids"],
- output_names=["last_hidden_state", "pooler_output"],
- dynamic_axes={
- "input_ids": {0: "batch", 1: "sequence"},
- },
- opset=opset,
- )
- del pipeline.text_encoder
-
- # # UNET
- if sd_xl:
- controlnets = torch.nn.ModuleList(controlnets)
- unet_controlnet = UNet2DConditionXLControlNetModel(pipeline.unet, controlnets)
- unet_in_channels = pipeline.unet.config.in_channels
- unet_sample_size = pipeline.unet.config.sample_size
- text_hidden_size = 2048
- img_size = 8 * unet_sample_size
- unet_path = output_path / "unet" / "model.onnx"
-
- onnx_export(
- unet_controlnet,
- model_args=(
- torch.randn(2, unet_in_channels, unet_sample_size, unet_sample_size).to(device=device, dtype=dtype),
- torch.tensor([1.0]).to(device=device, dtype=dtype),
- torch.randn(2, num_tokens, text_hidden_size).to(device=device, dtype=dtype),
- torch.randn(len(controlnets), 2, 3, img_size, img_size).to(device=device, dtype=dtype),
- torch.randn(len(controlnets), 1).to(device=device, dtype=dtype),
- torch.randn(2, 1280).to(device=device, dtype=dtype),
- torch.rand(2, 6).to(device=device, dtype=dtype),
- ),
- output_path=unet_path,
- ordered_input_names=[
- "sample",
- "timestep",
- "encoder_hidden_states",
- "controlnet_conds",
- "conditioning_scales",
- "text_embeds",
- "time_ids",
- ],
- output_names=["noise_pred"], # has to be different from "sample" for correct tracing
- dynamic_axes={
- "sample": {0: "2B", 2: "H", 3: "W"},
- "encoder_hidden_states": {0: "2B"},
- "controlnet_conds": {1: "2B", 3: "8H", 4: "8W"},
- "text_embeds": {0: "2B"},
- "time_ids": {0: "2B"},
- },
- opset=opset,
- use_external_data_format=True, # UNet is > 2GB, so the weights need to be split
- )
- unet_model_path = str(unet_path.absolute().as_posix())
- unet_dir = os.path.dirname(unet_model_path)
- # optimize onnx
- shape_inference.infer_shapes_path(unet_model_path, unet_model_path)
- unet_opt_graph = optimize(onnx.load(unet_model_path), name="Unet", verbose=True)
- # clean up existing tensor files
- shutil.rmtree(unet_dir)
- os.mkdir(unet_dir)
- # collate external tensor files into one
- onnx.save_model(
- unet_opt_graph,
- unet_model_path,
- save_as_external_data=True,
- all_tensors_to_one_file=True,
- location="weights.pb",
- convert_attribute=False,
- )
- del pipeline.unet
- else:
- controlnets = torch.nn.ModuleList(controlnets)
- unet_controlnet = UNet2DConditionControlNetModel(pipeline.unet, controlnets)
- unet_in_channels = pipeline.unet.config.in_channels
- unet_sample_size = pipeline.unet.config.sample_size
- img_size = 8 * unet_sample_size
- unet_path = output_path / "unet" / "model.onnx"
-
- onnx_export(
- unet_controlnet,
- model_args=(
- torch.randn(2, unet_in_channels, unet_sample_size, unet_sample_size).to(device=device, dtype=dtype),
- torch.tensor([1.0]).to(device=device, dtype=dtype),
- torch.randn(2, num_tokens, text_hidden_size).to(device=device, dtype=dtype),
- torch.randn(len(controlnets), 2, 3, img_size, img_size).to(device=device, dtype=dtype),
- torch.randn(len(controlnets), 1).to(device=device, dtype=dtype),
- ),
- output_path=unet_path,
- ordered_input_names=[
- "sample",
- "timestep",
- "encoder_hidden_states",
- "controlnet_conds",
- "conditioning_scales",
- ],
- output_names=["noise_pred"], # has to be different from "sample" for correct tracing
- dynamic_axes={
- "sample": {0: "2B", 2: "H", 3: "W"},
- "encoder_hidden_states": {0: "2B"},
- "controlnet_conds": {1: "2B", 3: "8H", 4: "8W"},
- },
- opset=opset,
- use_external_data_format=True, # UNet is > 2GB, so the weights need to be split
- )
- unet_model_path = str(unet_path.absolute().as_posix())
- unet_dir = os.path.dirname(unet_model_path)
- # optimize onnx
- shape_inference.infer_shapes_path(unet_model_path, unet_model_path)
- unet_opt_graph = optimize(onnx.load(unet_model_path), name="Unet", verbose=True)
- # clean up existing tensor files
- shutil.rmtree(unet_dir)
- os.mkdir(unet_dir)
- # collate external tensor files into one
- onnx.save_model(
- unet_opt_graph,
- unet_model_path,
- save_as_external_data=True,
- all_tensors_to_one_file=True,
- location="weights.pb",
- convert_attribute=False,
- )
- del pipeline.unet
-
- # VAE ENCODER
- vae_encoder = pipeline.vae
- vae_in_channels = vae_encoder.config.in_channels
- vae_sample_size = vae_encoder.config.sample_size
- # need to get the raw tensor output (sample) from the encoder
- vae_encoder.forward = lambda sample: vae_encoder.encode(sample).latent_dist.sample()
- onnx_export(
- vae_encoder,
- model_args=(torch.randn(1, vae_in_channels, vae_sample_size, vae_sample_size).to(device=device, dtype=dtype),),
- output_path=output_path / "vae_encoder" / "model.onnx",
- ordered_input_names=["sample"],
- output_names=["latent_sample"],
- dynamic_axes={
- "sample": {0: "batch", 1: "channels", 2: "height", 3: "width"},
- },
- opset=opset,
- )
-
- # VAE DECODER
- vae_decoder = pipeline.vae
- vae_latent_channels = vae_decoder.config.latent_channels
- # forward only through the decoder part
- vae_decoder.forward = vae_encoder.decode
- onnx_export(
- vae_decoder,
- model_args=(
- torch.randn(1, vae_latent_channels, unet_sample_size, unet_sample_size).to(device=device, dtype=dtype),
- ),
- output_path=output_path / "vae_decoder" / "model.onnx",
- ordered_input_names=["latent_sample"],
- output_names=["sample"],
- dynamic_axes={
- "latent_sample": {0: "batch", 1: "channels", 2: "height", 3: "width"},
- },
- opset=opset,
- )
- del pipeline.vae
-
- del pipeline
-
-
-if __name__ == "__main__":
- parser = argparse.ArgumentParser()
-
- parser.add_argument("--sd_xl", action="store_true", default=False, help="SD XL pipeline")
-
- parser.add_argument(
- "--model_path",
- type=str,
- required=True,
- help="Path to the `diffusers` checkpoint to convert (either a local directory or on the Hub).",
- )
-
- parser.add_argument(
- "--controlnet_path",
- nargs="+",
- required=True,
- help="Path to the `controlnet` checkpoint to convert (either a local directory or on the Hub).",
- )
-
- parser.add_argument("--output_path", type=str, required=True, help="Path to the output model.")
-
- parser.add_argument(
- "--opset",
- default=14,
- type=int,
- help="The version of the ONNX operator set to use.",
- )
- parser.add_argument("--fp16", action="store_true", default=False, help="Export the models in `float16` mode")
-
- args = parser.parse_args()
-
- convert_models(args.model_path, args.controlnet_path, args.output_path, args.opset, args.fp16, args.sd_xl)
diff --git a/spaces/panchajanya1999/chatgenius/README.md b/spaces/panchajanya1999/chatgenius/README.md
deleted file mode 100644
index 27e3e8087ab4735ce85e3f20052bdf56e6888618..0000000000000000000000000000000000000000
--- a/spaces/panchajanya1999/chatgenius/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Chatgenius
-emoji: 🐨
-colorFrom: gray
-colorTo: green
-sdk: gradio
-sdk_version: 3.23.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/pdjewell/sommeli_ai/app_old.py b/spaces/pdjewell/sommeli_ai/app_old.py
deleted file mode 100644
index cb106be38ee72179da7a9273659907cdf069ffbe..0000000000000000000000000000000000000000
--- a/spaces/pdjewell/sommeli_ai/app_old.py
+++ /dev/null
@@ -1,236 +0,0 @@
-import numpy as np
-import pandas as pd
-import os
-from PIL import Image
-import streamlit as st
-from streamlit import components
-from datasets import Dataset, load_dataset, load_from_disk
-import faiss
-from scripts.preprocessing import preprocess
-
-# App config
-icon = Image.open('./images/wine_icon.png')
-st.set_page_config(page_title="Sommeli-AI",
- page_icon=icon,
- layout="wide")
-hide_default_format = """
-
- """
-st.markdown(hide_default_format, unsafe_allow_html=True)
-
-# App functions
-@st.cache_data
-def read_data(ds_path=None):
-
- if ds_path is not None:
- # Read in hf file
- embeddings_dataset = load_from_disk(ds_path)
- else:
- embeddings_dataset = load_dataset("pdjewell/sommeli_ai", split="train")
-
- # Convert to pandas df
- embeddings_dataset.set_format("pandas")
- df = embeddings_dataset[:]
-
- # preprocess data (add type col, remove dups)
- df = preprocess(df)
-
- return df
-
-
-def get_neighbours(df, query_embedding, k=6,
- metric='inner'):
-
- # convert from pandas df to hf ds
- ds = Dataset.from_pandas(df)
- ds.reset_format()
- ds = ds.with_format("np")
-
- # add faiss index
- if metric == 'inner':
- ds.add_faiss_index(column="embeddings",
- metric_type=faiss.METRIC_INNER_PRODUCT)
- else:
- ds.add_faiss_index(column="embeddings",
- metric_type=faiss.METRIC_L2)
-
- scores, samples = ds.get_nearest_examples(
- "embeddings", query_embedding, k=k)
-
- samples.pop('embeddings')
- samples.pop('__index_level_0__')
-
- return scores, samples
-
-
-def filter_df_search(df: pd.DataFrame) -> pd.DataFrame:
-
- modify_search = st.checkbox("🔍 Further filter search selection")
-
- if not modify_search:
- return df
-
- df = df.copy()
-
- modification_container_search = st.container()
-
- with modification_container_search:
- to_filter_columns = st.multiselect("Filter on:",
- ['Province', 'Region', 'Winery','Score', 'Price'],
- key='search')
-
- for column in to_filter_columns:
- if column in ['Score', 'Price']: # Use slider for 'points' and 'price'
- min_val = 0
- max_val = int(df[column].max())
- user_input = st.slider(f"Values for {column}", min_val, max_val, (min_val, max_val))
- df = df[(df[column] >= user_input[0]) & (df[column] <= user_input[1])]
- elif column in ['Country', 'Province', 'Region', 'Variety', 'Winery']: # Use multiselect for these columns
- unique_values = df[column].dropna().unique()
- default_values = [unique_values[0]] if len(unique_values) > 0 else [] # Select only the first unique value if it exists
- user_input = st.multiselect(f"Values for {column}", unique_values, default_values)
- df = df[df[column].isin(user_input)]
-
- return df
-
-
-def filter_df_recs(df: pd.DataFrame) -> pd.DataFrame:
-
- modify_recs = st.checkbox("🔍 Filter recommendation results")
-
- if not modify_recs:
- return df
-
- df = df.copy()
-
- modification_container_recs = st.container()
-
- with modification_container_recs:
-
- to_filter_columns2 = st.multiselect("Filter on:",
- ['Country','Province', 'Region', 'Variety', 'Winery',
- 'Score', 'Price'],
- key='recs')
-
- for column in to_filter_columns2:
- if column in ['Score', 'Price']: # Use slider for 'points' and 'price'
- min_val = 0
- max_val = int(df[column].max())
- user_input = st.slider(f"Values for {column}", min_val, max_val, (min_val, max_val))
- df = df[(df[column] >= user_input[0]) & (df[column] <= user_input[1])]
- elif column in ['Country', 'Province', 'Region', 'Variety', 'Winery']: # Use multiselect for these columns
- unique_values = df[column].dropna().unique()
- default_values = [unique_values[0]] if len(unique_values) > 0 else [] # Select only the first unique value if it exists
- user_input = st.multiselect(f"Values for {column}", unique_values, default_values)
- df = df[df[column].isin(user_input)]
-
- return df
-
-
-if __name__ == "__main__":
- st.title("🍷 Sommeli-AI")
- col1, col2 = st.columns([0.6,0.4], gap="medium")
-
- # Read in data
- ds_path = "./data/wine_ds.hf"
- df = read_data(ds_path=None)
-
- with col2:
- st.header("Explore the world of wine 🌍")
- wine_plot = st.radio('Select plot type:', ['2D','3D'],
- label_visibility = "hidden",
- horizontal=True)
- st.text("Click the legend categories to filter")
-
- # Load the HTML file
- with open('./images/px_2d.html', 'r') as file:
- plot2d_html = file.read()
- # Load the HTML file
- with open('./images/px_3d.html', 'r') as file:
- plot3d_html = file.read()
- # Display the HTML plot in the Streamlit app
- if wine_plot == '2D':
- components.v1.html(plot2d_html, width=512, height=512)
- elif wine_plot == '3D':
- components.v1.html(plot3d_html, width=512, height=512)
-
- with col1:
-
- # Select all wine types initially
- st.header("Search for similar wines 🥂")
- # Select wine type: default is all
- wine_types = df['Type'].unique()
- selected_wine_types = st.multiselect("Select category 👇", wine_types, default=wine_types)
- df = df[df['Type'].isin(selected_wine_types)]
- subcol1, subcol2 = st.columns([0.5,0.5], gap="small")
- with subcol1:
- # Select wine variety: default is all
- wine_vars = df['Variety'].unique()
- selected_wine_vars = st.multiselect("Narrow down the variety 🍇",['Select all'] + list(wine_vars),
- default = 'Select all')
- if "Select all" in selected_wine_vars:
- df_search = df
- else:
- df_search = df[df['Variety'].isin(selected_wine_vars)]
-
- with subcol2:
- # Select the country: default is all
- countries = df_search['Country'].unique()
- selected_countries = st.multiselect("Narrow down the country 🌎",['Select all'] + list(countries),
- default = 'Select all')
- if "Select all" in selected_countries:
- df_search = df_search
- else:
- df_search = df_search[df_search['Country'].isin(selected_countries)]
-
- # Add additional filters
- df_search = filter_df_search(df_search)
-
- # Create a search bar for the wine 'title'
- selected_wine = st.selectbox("Search for and select a wine 👇", [''] + list(df_search["Title"].unique()))
-
- if selected_wine:
- # Get the embedding for selected_wine
- query_embedding = df.loc[df['Title']==selected_wine, 'embeddings'].iloc[0]
-
- tasting_notes = df.loc[df['Title']==selected_wine, 'Tasting notes'].iloc[0]
- st.write(f"Tasting notes: {tasting_notes}")
-
- # CSS to inject contained in a string
- hide_table_row_index = """
-
- """
- # Inject CSS with Markdown
- st.markdown(hide_table_row_index, unsafe_allow_html=True)
-
- # Display selected wine
- st.header(" 🍷 Your selected wine")
- selected_cols = ['Title','Country','Province','Region','Winery',
- 'Variety','Tasting notes','Score']
- st.table(df.loc[df['Title']==selected_wine, selected_cols].fillna(""))
-
- # Slider for results to show
- k = st.slider(f"Choose how many similar wines to show 👇", 1, 10, value=4)
-
- # Filter recommendation results
- df_results = filter_df_recs(df)
-
- # Display results as table
- if st.button("🔘 Press me to generate similar tasting wines"):
- # Get neighbours
- scores, samples = get_neighbours(df_results, query_embedding,
- k=k+1, metric='l2')
- recs_df = pd.DataFrame(samples).fillna("")
- recs_df = recs_df.fillna(" ")
- # Display results
- st.header(f"🍾 Top {k} similar tasting wines")
- st.table(recs_df.loc[1:,selected_cols])
-
- else:
- print("Awaiting selection")
diff --git a/spaces/pixiou/bingo/src/components/chat-header.tsx b/spaces/pixiou/bingo/src/components/chat-header.tsx
deleted file mode 100644
index c6664b8dee61179f844d45c5bd650518fc2cb4c2..0000000000000000000000000000000000000000
--- a/spaces/pixiou/bingo/src/components/chat-header.tsx
+++ /dev/null
@@ -1,12 +0,0 @@
-import LogoIcon from '@/assets/images/logo.svg'
-import Image from 'next/image'
-
-export function ChatHeader() {
- return (
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diff --git a/spaces/quidiaMuxgu/Expedit-SAM/Idhayame Idhayame Ennai Maranthathu Yeno Mp3 Song.md b/spaces/quidiaMuxgu/Expedit-SAM/Idhayame Idhayame Ennai Maranthathu Yeno Mp3 Song.md
deleted file mode 100644
index 11e688b37efdaba53bba0d707f1eabb4976e80f8..0000000000000000000000000000000000000000
--- a/spaces/quidiaMuxgu/Expedit-SAM/Idhayame Idhayame Ennai Maranthathu Yeno Mp3 Song.md
+++ /dev/null
@@ -1,58 +0,0 @@
-idhayame idhayame ennai maranthathu yeno mp3 song
-
-This amazing music of idhayame idhayame ennai is provided for personal use only, if any third partys appears in the content be aware it is illegal to use and distribute.
-
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-
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-
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-
-"Now what happened to that doctor who prescribed Rafi for my diabetes!"
-
-- Rafi
-
-Music / Drama / Short
-
-List of songs -
-
-Idhayame Idhayame Ennai Ringtone -
-
-Indian movie and a special song by the singer known as Rafi.
-
-The link brings the song to the phone, the ringtone is stored in a mp3 file which can be played as ringtone.
-
-Purba Jadoo -
-
-Purba Jadoo Ringtone -
-
-Ek Bhool Na Koi -
-
-The first of two Rafi kathre man movies where he sings two songs.
-
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-
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-
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diff --git a/spaces/radames/UserControllableLT-Latent-Transformer/expansion/utils/pfm.py b/spaces/radames/UserControllableLT-Latent-Transformer/expansion/utils/pfm.py
deleted file mode 100644
index 65a3dbb10ae96a72110294feb7cdc8df9d9c8b0d..0000000000000000000000000000000000000000
--- a/spaces/radames/UserControllableLT-Latent-Transformer/expansion/utils/pfm.py
+++ /dev/null
@@ -1,79 +0,0 @@
-import re
-import numpy as np
-import sys
-
-def readPFM(file):
- file = open(file, 'rb')
-
- color = None
- width = None
- height = None
- scale = None
- endian = None
-
- header = file.readline().rstrip()
- if (sys.version[0]) == '3':
- header = header.decode('utf-8')
- if header == 'PF':
- color = True
- elif header == 'Pf':
- color = False
- else:
- raise Exception('Not a PFM file.')
-
- if (sys.version[0]) == '3':
- dim_match = re.match(r'^(\d+)\s(\d+)\s$', file.readline().decode('utf-8'))
- else:
- dim_match = re.match(r'^(\d+)\s(\d+)\s$', file.readline())
- if dim_match:
- width, height = map(int, dim_match.groups())
- else:
- raise Exception('Malformed PFM header.')
-
- if (sys.version[0]) == '3':
- scale = float(file.readline().rstrip().decode('utf-8'))
- else:
- scale = float(file.readline().rstrip())
-
- if scale < 0: # little-endian
- endian = '<'
- scale = -scale
- else:
- endian = '>' # big-endian
-
- data = np.fromfile(file, endian + 'f')
- shape = (height, width, 3) if color else (height, width)
-
- data = np.reshape(data, shape)
- data = np.flipud(data)
- return data, scale
-
-
-def writePFM(file, image, scale=1):
- file = open(file, 'wb')
-
- color = None
-
- if image.dtype.name != 'float32':
- raise Exception('Image dtype must be float32.')
-
- image = np.flipud(image)
-
- if len(image.shape) == 3 and image.shape[2] == 3: # color image
- color = True
- elif len(image.shape) == 2 or len(image.shape) == 3 and image.shape[2] == 1: # greyscale
- color = False
- else:
- raise Exception('Image must have H x W x 3, H x W x 1 or H x W dimensions.')
-
- file.write('PF\n' if color else 'Pf\n')
- file.write('%d %d\n' % (image.shape[1], image.shape[0]))
-
- endian = image.dtype.byteorder
-
- if endian == '<' or endian == '=' and sys.byteorder == 'little':
- scale = -scale
-
- file.write('%f\n' % scale)
-
- image.tofile(file)
diff --git a/spaces/raedeXanto/academic-chatgpt-beta/Age Of Empires II HD V5.8 Cheat Engine A Complete Tutorial for Beginners and Experts.md b/spaces/raedeXanto/academic-chatgpt-beta/Age Of Empires II HD V5.8 Cheat Engine A Complete Tutorial for Beginners and Experts.md
deleted file mode 100644
index 9ab5949e51ff60960c8dbf1a3c067fd270f94075..0000000000000000000000000000000000000000
--- a/spaces/raedeXanto/academic-chatgpt-beta/Age Of Empires II HD V5.8 Cheat Engine A Complete Tutorial for Beginners and Experts.md
+++ /dev/null
@@ -1,229 +0,0 @@
-
-Age of Empires II HD V5.8 Cheat Engine: How to Hack the Game with Ease
- Introduction
- Age Of Empires II HD V5.8 Cheat Engine
- What is Age of Empires II HD?
- What is Cheat Engine?
- Why use Cheat Engine for Age of Empires II HD?
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-
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-How to hack Age of Empires II HD with Cheat Engine
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-How to avoid detection and ban with Cheat Engine 6.7 in Age of Empires II HD
-How to report bugs and issues with Cheat Engine 6.7 in Age of Empires II HD
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- How to use Cheat Engine for Age of Empires II HD
- Download and install Cheat Engine
- Run the game and Cheat Engine
- Select the game process in Cheat Engine
-
-
- Load a cheat table or scan for values
-
-
-
-
- Activate the cheats you want
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-
- Examples of cheats you can use with Cheat Engine
- Minimum Resources
- God Mode
- Instant Construction/Production/Research
- Unit and Resource Editor
- Conclusion
- Summary of the article
- Disclaimer and warning
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- FAQs
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1 | -GroundingDINO-T | -Swin-T | -O365,GoldG,Cap4M | -48.4 (zero-shot) / 57.2 (fine-tune) | -Github link | HF link | -link | -
If you are a fan of survival games, you might have heard of Ark Survival Evolved, a popular game that lets you explore and survive in a prehistoric world full of dinosaurs and other creatures. But did you know that you can make your gaming experience even more fun and exciting by using Ark Survival Evolved Mod Apk? In this article, we will tell you everything you need to know about this modded version of the game, including its features, functions, benefits, and how to download and install it on your device. Read on to find out more!
-Ark Survival Evolved is an action-packed survival game developed by Studio Wildcard. It was released in 2017 for various platforms, including Android, iOS, Windows, PlayStation, Xbox, and Nintendo Switch. The game is set in a massive open world that is filled with over 80 different species of dinosaurs and other prehistoric animals. You can tame, breed, ride, and fight with these creatures as you explore the land, sea, and air.
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The game also has a crafting system that allows you to create weapons, tools, armor, buildings, and other items from the resources you gather. You can also customize your character's appearance, skills, and attributes. You can play the game solo or with other players online in various modes, such as PvP, PvE, co-op, or tribe wars. The game has a story mode that involves finding clues and solving mysteries about the origin and purpose of the Ark, a mysterious island that holds many secrets.
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While using Ark Survival Evolved Mod Apk can be fun and exciting, you also need to be careful and smart about it. Here are some precautions and tips that you should keep in mind when using the mod apk:
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-While using Ark Survival Evolved Mod Apk can give you unlimited resources and max level in the game, you might wonder how to use them effectively and efficiently. Here are some of the best ways to use them in the game:
-Ark Survival Evolved Mod Apk is a great way to enjoy playing Ark Survival Evolved on your Android device. It gives you many features and functions that can make your gameplay easier and more enjoyable. Some of these features and functions are:
-By using Ark Survival Evolved Mod Apk, you can have more fun and excitement while playing Ark Survival Evolved. You can also save time, money, and effort while playing the game. You can also experience more challenges, adventures, and discoveries while playing the game.
-If you are interested in trying out Ark Survival Evolved Mod Apk, you can download it from this link or from any other website online. You can also follow the steps and tips we have provided above to download and install it on your device. You can also use the mod apk safely and effectively by following the precautions and tips we have provided above.
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401be4b1e0Bus Simulator Indonesia is a popular game that lets you experience what it likes being a bus driver in Indonesia. But did you know that you can also customize your bus and add more features to the game by using mods? Mods are modifications that change the game in some way, such as adding new vehicles, maps, sounds, graphics, and more. In this article, we will show you how to download mods for bus simulator Indonesia and enjoy the game even more.
-Bus Simulator Indonesia (aka BUSSID) is a game developed by Maleo that was released in 2017. It is one of the only bus simulator games with the most authentic Indonesian environment and culture. You can drive various types of buses, such as city buses, intercity buses, tourist buses, and even school buses. You can also design your own livery, honk your horn, and interact with other players online.
-Download Zip ✔ https://ssurll.com/2uNUos
Some of the top features of Bus Simulator Indonesia are:
-Mods can enhance your gaming experience by adding more variety, realism, and fun to the game. You can drive different kinds of vehicles, such as trucks, cars, motorcycles, and even airplanes. You can also explore new maps, such as Bali, Jakarta, Surabaya, and more. You can also improve the graphics, sounds, physics, and performance of the game. Mods can also fix some bugs and glitches that may occur in the game.
-Finding mods for Bus Simulator Indonesia is not hard. There are many sources of mods that you can access online. However, you need to be careful when downloading mods from unknown or untrusted sources, as they may contain viruses or malware that can harm your device or data. Here are some of the best sources of mods for Bus Simulator Indonesia:
-Name | Description | URL |
---|---|---|
MODBUSSID.CO.ID | This is one of the most popular sites that provides hundreds of MOD BUSSID with various types of vehicles, such as buses, trucks, cars, and motorcycles. You can download MOD BUSSID easily with direct download links and no password required. | [4](https://modbussid.co.id/) |
MODBUSSIDINDONESIA.CO.ID | This is another site that offers a lot of MOD BUSSID with different categories, such as bus full strobo, bus full animasi, truck full animasi, mobil full animasi, and more. You can also find livery collections and tutorials on how to install MOD BUSSID on this site. | [5](https://modbussidindonesia.co.id/) |
BUS-SIMULATOR.ID | This is the official site of the game developer Maleo. You can find some official MOD BUSSID that are compatible with the latest version of the game. You can also find some tips and tricks, news, and updates about the game on this site. | [6](https://bus-simulator.id/) |
MODSFILE.COM | This is a site that provides various mods for different games, including Bus Simulator Indonesia. You can find mods for vehicles, maps, skins, sounds, and more. You can also upload your own mods and share them with other players. | [7](https://modsfile.com/category/bus-simulator-indonesia-mods/) |
There are many types of mods that you can use for Bus Simulator Indonesia. Some of the most common ones are:
-Installing mods for Bus Simulator Indonesia is not difficult. However, you need to follow some steps carefully to avoid any errors or problems. Here are the steps to install mods for Bus Simulator Indonesia:
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-If you are a fan of Genshin Impact, the popular open-world action RPG game, you might be interested in reading its official manga adaptation. The Genshin Impact manga is a prequel to the game's main story, featuring the history and secrets of the seven nations and the elemental archons that rule them. In this article, we will tell you everything you need to know about the Genshin Impact manga, including what it is, where to read it online, how to download it offline, and why you should read it.
-The Genshin Impact manga is a comic series based on the game of the same name, developed by miHoYo. The manga is produced by HoYoverse and illustrated by multiple artists, with each chapter having different teams of varying artists. The manga is set before the events of the game's main story, and explores the background and lore of the world of Teyvat, a land blessed by the seven elemental archons.
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The manga follows the adventures of various characters from different nations, as they face the threats and challenges posed by the domineering Fatui, an organization that seeks to manipulate the archons and their powers for their own agenda. The manga also reveals the origins and motivations of some of the game's main characters, such as Diluc, Kaeya, Jean, Lisa, Amber, Venti, and more.
-The manga is divided into several chapters, each focusing on a different nation or event. The chapters are:
-Chapter | -Title | -Description | -
---|---|---|
Prologue | -Songs of the Wind | -The origin of Mondstadt, the city of wind, and how it was liberated by Vennessa and Barbatos. | -
1 | -Bad Wine | -The introduction of Diluc and Kaeya, two knights of Favonius who investigate a mysterious fire incident caused by Il Dottore, a Fatui envoy. | -
2 | -Flame Born | -The aftermath of Diluc's confrontation with Il Dottore, and how it changed his life forever. | -
3 | -Lost and Found | -The introduction of Amber, an outrider who meets a mysterious girl named Klee who is looking for something in Mondstadt. | -
4 | -Surprise Finding | -The introduction of Jean and Lisa, two senior knights who are also investigating the fire incident and its connection to a legendary beast called the Serpent of Black Fire. | -
5 | -Dangerous Grounds | -The continuation of Amber's adventure with Klee, as they encounter a dangerous ruin guard in their search. | -
6 | -A New Storm Approaches | -The introduction of Venti, a bard who claims to be an old friend of Barbatos, and his involvement in Mondstadt's history. | -
And so on until chapter 17 (as of June 2023).
-The manga features a diverse cast of characters from different nations, each with their own personality, backstory, and elemental affinity. The elements are the fundamental forces of nature that govern Teyvat, and they are: Anemo (wind), Pyro (fire), Hydro (water), Cryo (ice), Electro (lightning), Dendro (nature), and Geo (earth). Each character can use their elemental power to perform various skills and attacks, as well as combine them with other elements to create elemental reactions that have different effects. For example, Pyro and Hydro can create Vaporize, which deals extra damage; Electro and Cryo can create Superconduct, which lowers the enemy's defense; and Anemo and Geo can create Swirl, which spreads the other element around. The manga also introduces some of the game's mechanics and features, such as the Vision, the Archon Quest, the Abyss Order, and the Traveler. The Vision is a special gem that grants the wielder the ability to use elemental power, and it is bestowed by the archons to those who have proven themselves worthy. The Archon Quest is a series of missions that involve the main story of the game, where the Traveler, a mysterious outsider who can switch between elements, seeks to find their lost sibling and unravel the secrets of Teyvat. The Abyss Order is a mysterious organization that opposes the archons and their followers, and they are led by an unknown figure called the Prince of Darkness. The Traveler is the protagonist of the game and the manga, who can be either male or female depending on the player's choice.
If you want to read the Genshin Impact manga online, you have several options to choose from. Here are some of the most popular and reliable platforms where you can find the manga:
-The easiest and most convenient way to read the Genshin Impact manga is to visit its official website: https://genshin.mihoyo.com/en/manga. Here, you can find all the chapters of the manga in high quality and in multiple languages, such as English, Japanese, Chinese, Korean, French, German, Spanish, Portuguese, Russian, Thai, Indonesian, and Vietnamese. You can also leave comments and feedback on each chapter, as well as share them on social media. The website is updated regularly with new chapters and announcements.
-Another popular platform where you can read the Genshin Impact manga is Webtoon: https://www.webtoons.com/en/action/genshin-impact/list?title_no=2459. Webtoon is a global digital comic service that hosts thousands of comics in various genres and languages. The Genshin Impact manga is available on Webtoon in English, Japanese, Chinese (Simplified and Traditional), Korean, French, German, Spanish (Spain and Latin America), Portuguese (Brazil), Russian, Thai, Indonesian, and Vietnamese. You can also rate and review each chapter, as well as interact with other readers and fans.
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If you are a subscriber of Crunchyroll: https://www.crunchyroll.com/comics/manga/genshin-impact/volumes , you can also read the Genshin Impact manga on their website or app. Crunchyroll is a streaming service that offers anime, manga, drama, games, and more. The Genshin Impact manga is available on Crunchyroll in English only. You can also watch some of the game's trailers and videos on their platform.
-If you want to download the Genshin Impact manga offline for later reading or sharing, you have two options to do so:
-One way to download the Genshin Impact manga offline is to use Dropbox: https://www.dropbox.com/sh/4xw0j5q0j7l1f8c/AADZ6aXUWQzLlYmZKJFQgQfka?dl=0 . Dropbox is a cloud storage service that allows you to store and access your files from anywhere. Here, you can find all the chapters of the manga in PDF format in English only. You can download them individually or as a whole folder. You can also view them online or offline using any PDF reader.
-Another way to download the Genshin Impact manga offline is to use Hoyoverse: https://hoyolab.com/genshin/article/1028 . Hoyoverse is a fan community platform for Genshin Impact players and fans. Here, you can find all the chapters of the manga in JPG format in multiple languages such as English, Japanese, Chinese, Korean, French, German, Spanish, Portuguese, Russian, Thai, Indonesian, and Vietnamese. You can download them individually or as a whole folder. You can also view them online or offline using any image viewer.
-Now that you know what the Genshin Impact manga is and where to read and download it, you might be wondering why you should read it in the first place. Well, here are some of the reasons why you should give it a try:
-If you are curious about the history and secrets of Teyvat and its inhabitants, the manga is a great source of information and insight. The manga reveals some of the events and characters that shaped the world of the game, such as the origin of Mondstadt and its archon, the conflict between Diluc and Kaeya, the role of the Fatui and their envoys, and more. The manga also foreshadows some of the future developments and regions that will be added to the game, such as Inazuma, Sumeru, Fontaine, Natlan, and Snezhnaya.
-The manga is a visual treat for the eyes, as it showcases the beautiful scenery and landscapes of Teyvat, as well as the detailed designs and expressions of the characters. The manga also delivers some thrilling and epic action scenes, as the characters use their elemental powers and skills to fight against enemies and monsters. The manga captures the essence and style of the game's graphics and animations, while adding its own flair and creativity.
-The manga is not just a retelling or adaptation of the game's story, but also a supplement and expansion of it. The manga introduces some new characters that are not yet available or playable in the game, such as Vennessa, Klee, Dainsleif, Scaramouche, Signora, La Signora, Tartaglia, Zhongli, Xiao, Ganyu, Ayaka, Yae Miko, Baal, Sara, Kokomi, Thoma, Gorou, Yae Sakura ,and more. The manga also depicts some events that are not shown or mentioned in the game, such as the liberation of Mondstadt by Vennessa and Barbatos ,the fire incident caused by Il Dottore ,the search for Klee's treasure ,the origin of Venti's lyre ,and more.
-The Genshin Impact manga is a must-read for any fan of the game or anyone who enjoys fantasy and adventure stories. The manga offers a rich and immersive experience that complements and enhances the game's story and gameplay. The manga is easy to access online or offline through various platforms and formats. The manga is also updated regularly with new chapters and content. If you want to dive deeper into the world of Teyvat and its mysteries ,the Genshin Impact manga is for you!
-Here are some of the frequently asked questions about the Genshin Impact manga:
-A: Yes ,the Genshin Impact manga is canon ,as it is officially produced by miHoYo ,the developer of the game. The manga follows the same timeline and lore as the game ,and it is supervised by miHoYo's writers and artists.
-A: The Genshin Impact manga is updated every week ,usually on Fridays. However ,there may be some delays or changes depending on miHoYo's schedule or plans.
-A: As of June 2023 ,there are 17 chapters in the Genshin Impact manga ,plus a prologue chapter. However ,the number may vary depending on the platform or language you are reading from.
-A: Each chapter of the Genshin Impact manga varies in length ,but they are usually around 20 to 30 pages long.
-A: You can support the Genshin Impact manga by reading it from its official website or other authorized platforms ,such as Webtoon or Crunchyroll. You can also leave comments ,feedback ,ratings ,and reviews on each chapter ,as well as share them on social media. You can also support the game by playing it and spending on its in-game currency, Primogems, which can be used to obtain new characters, weapons, and items.
401be4b1e0If you are a fan of football games, you might have heard of FIFA 2023 Mod FIFA 16, a modded version of FIFA 16 that features updated kits, transfers, stadiums, and graphics for the 2022/23 season. This game is not available on the Google Play Store, but you can download and install it manually on your Android device. In this article, we will show you what is FIFA 2023 Mod FIFA 16, what are its new features, and how to download and install it on your Android device.
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FIFA 2023 Mod FIFA 16 is a fan-made modification of FIFA 16, one of the most popular football games for Android devices. It is developed by a group of modders who have updated the game with the latest kits, transfers, stadiums, and graphics for the upcoming season. The game also includes some features from FIFA 23, such as HyperMotion2 Technology, both men’s and women’s FIFA World Cup™ tournaments, cross-play features, and more.
-There are several advantages of playing FIFA 2023 Mod FIFA 16 over the official version of FIFA 16 or FIFA 23. Some of them are:
-As mentioned above, FIFA 2023 Mod FIFA 16 has some new features that make it more enjoyable and realistic than the official version of FIFA 16 or FIFA 23. Here is a summary of the new features of FIFA 2023 Mod FIFA 16:
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Feature | -FIFA 2023 Mod FIFA 16 | -FIFA 16 | -FIFA 23 | -
---|---|---|---|
HyperMotion2 Technology | -Yes | -No | -Yes | -
Both men’s and women’s FIFA World Cup™ tournaments | -Yes (post-launch) | -No | -No (only men's) | -
Cross-play features | -Yes (same generation) | -No | -No (only same platform) | -
Updated kits, transfers, stadiums, and graphics for the 2022/23 season | -Yes | -No (only for the 2015/16 season) | -No (only for the 2021/22 season) | -
Women’s club teams | -Yes (early 2023) | -No (only national teams) | -No (only national teams) | -
Offline mode | -Yes (all modes) | -No (only some modes) | -No (only some modes) |
If you want to play FIFA 2023 Mod FIFA 16 on your Android device, you need to download and install the APK, OBB, and data files of the game manually. Here is a step-by-step guide on how to do that:
-Before you download and install FIFA 2023 Mod FIFA 16 on your Android device, you should be aware of some requirements and precautions. Here is a list of them:
-To give you an idea of how the game looks like on an Android device, here is a screenshot of FIFA 2023 Mod FIFA 16 running on a Samsung Galaxy S10:
-In conclusion, FIFA 2023 Mod FIFA 16 is a modded version of FIFA 16 that features updated kits, transfers, stadiums, and graphics for the 2022/23 season. It also includes some features from FIFA 23, such as HyperMotion2 Technology, both men’s and women’s FIFA World Cup™ tournaments, cross-play features, and more. You can download and install it manually on your Android device by following the steps in this article. You can also compare the features of FIFA 2023 Mod FIFA 16, FIFA 16, and FIFA 23 in the table above.
-If you are a fan of football games, we recommend you to try out FIFA 2023 Mod FIFA 16 on your Android device. It is one of the best football games for Android devices that offers a realistic and immersive football experience. You can play offline or online with friends or other players who have the same modded version of the game. You can also customize your own kits, players, and teams with the Creation Centre. You can enjoy playing as women’s club teams for the first time in EA SPORTS™ history with the Barclays Women’s Super League and Division 1 Arkema, and the UEFA Women’s Champions League knockout stage coming to FIFA in early [user]( 2023. You can also experience the pinnacle of international football with both men’s and women’s FIFA World Cup™ tournaments as post-launch content updates at no additional cost.
-Here are some of the most frequently asked questions and answers about FIFA 2023 Mod FIFA 16:
-FIFA 2023 Mod FIFA 16 is not an official product of EA SPORTS™ or FIFA. It is a fan-made modification of FIFA 16 that uses the assets and data of the original game. Therefore, it is not legal to distribute or sell the modded game without the permission of the original developers. However, you can download and install it at your own risk for personal use only.
-FIFA 2023 Mod FIFA 16 is safe to play as long as you download and install it from a trusted source. However, you should be careful when downloading the files from online sources, as they might contain viruses or malware that can harm your device. You should also disable any antivirus or security apps that might interfere with the installation or running of the game. You should also backup your data and settings before installing the game, as it might overwrite or delete some files.
-FIFA 2023 Mod FIFA 16 is compatible with most Android devices that have at least 2 GB of RAM and 4 GB of free storage space. However, some devices might not be able to run the game smoothly or at all due to hardware limitations or software issues. You should check the requirements and precautions for installing the modded game before downloading and installing it on your device.
-FIFA 2023 Mod FIFA 16 is updated regularly by the modders who have developed it. You can check for updates on their official website or social media pages. You can also subscribe to their newsletter or notifications to get notified when a new update is available. To update the game, you need to download and install the latest version of the APK, OBB, and data files of the game manually.
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-If you are looking for a fast-paced and exciting action game with stunning graphics and smooth gameplay, you should check out Broken Dawn II. This game is a sequel to the popular Broken Dawn: Trauma, which is set in a post-apocalyptic world where a deadly virus has turned most people into zombies and mutants. You have to fight your way through hordes of enemies, using various weapons and skills, and save the survivors.
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Broken Dawn II is available for Android devices, and you can download the latest version 1.4.3 from the link below. This version comes with a mod that gives you infinite ammo and a mega mod that enhances your performance and abilities. You can enjoy the game without worrying about running out of bullets or getting killed easily.
-Some of the features of Broken Dawn II are:
-If you are ready to experience the thrill of Broken Dawn II, download the game now from the link below. You will need an Android device with version 4.1 or higher and at least 45 MB of free storage space. Enjoy!
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-The game has a rich and immersive story mode, where you can follow the main character's journey and learn more about the world and the virus. You can also play the survival mode, where you have to survive as long as possible against endless waves of enemies. Or you can challenge yourself in the boss mode, where you have to face the most dangerous and powerful enemies in the game.
-Broken Dawn II is a game that will keep you entertained for hours, with its addictive gameplay, stunning graphics, and varied content. It is also a game that will challenge your skills and reflexes, with its fast-paced action, diverse enemies, and difficult bosses. If you are a fan of action games, you should not miss Broken Dawn II.
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-``` 81aa517590Dil Dosti Etc is a 2007 Indian movie that explores the lives of two college students from different backgrounds and their views on love, friendship, politics and sex. The movie stars Imaad Shah as Apurv, a rich and carefree playboy who is bored of his life and seeks thrill in casual relationships, and Shreyas Talpade as Sanjay Mishra, a poor and ambitious student leader who dreams of becoming a politician and falls in love with a married woman. The movie also features Ishita Sharma, Nikita Anand and Smriti Mishra in supporting roles.
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The movie is directed by Manish Tiwary and written by Ishita Moitra. It has received mostly positive reviews from critics and audiences, who praised its realistic portrayal of youth culture, its witty dialogues and its bold themes. The movie has an IMDb rating of 6.9 out of 10 and a Rotten Tomatoes score of 74%.
-If you are looking for a way to watch Dil Dosti Etc online with English subtitles, you have several options. You can stream the movie on Amazon Prime Video or Lionsgate Play with a subscription, or you can watch it for free with ads on Hotstar. You can also rent or buy the movie on Google Play Movies or YouTube. Alternatively, you can download the movie with English subtitles from various torrent sites, but be careful of the legal and security risks involved.
-Dil Dosti Etc is a movie that will make you laugh, cry and think about the choices you make in life. It is a movie that will appeal to anyone who enjoys a good drama with a touch of comedy and romance. If you are looking for a movie that will entertain you and challenge you at the same time, Dil Dosti Etc is the one for you.
- -One of the highlights of Dil Dosti Etc is the soundtrack, which features songs by various artists such as Siddharth-Suhas, Agnee, Shantanu Moitra and Kailash Kher. The songs range from upbeat rock numbers to soulful ballads, and reflect the mood and theme of the movie. Some of the popular songs from the movie are "Dum Laga", "Lamha Ye Jayega Kahan", "Sambhalo Dil Ko" and "Man Moniye". The songs are available to listen on various music platforms such as Spotify, Gaana, JioSaavn and Apple Music.
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7b8c122e87Ganxsta Zolee és a Kartel is one of the most influential and successful hip hop groups in Hungary. Their 1999 album Helldorado is considered a classic of the genre, featuring hardcore rap lyrics, catchy hooks, and diverse beats. The album was re-released in 2018 as Helldorado Ãjratöltve, with remastered sound quality and a brand new track.
- -In this article, we will review the original album and its re-release, highlighting the best songs, the lyrical themes, and the impact of the group on the Hungarian rap scene.
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The original album was released in 1999 by Epic Records, and it was the third studio album by Ganxsta Zolee és a Kartel. The album consists of 13 tracks, with a total length of 54 minutes. The album title is a reference to the Wild West, and the cover art depicts the group members as outlaws in a desert landscape.
- -The album features guest appearances by Ambrus Rita, Siska Finuccsi, and O.J. Sámson, as well as samples from various movies and songs. The album showcases the group's versatility, as they rap over different styles of beats, from funk to rock to reggae. The album also contains some of their most popular songs, such as "A Jó, a Rossz és a Kartel", "A Való Világ", "Helldorado", and "Nincs Az A Csaj".
- - -The album's lyrics are mostly focused on the harsh realities of life in Hungary, especially in the capital city of Budapest. The group raps about poverty, violence, corruption, drugs, sex, and racism, using explicit language and vivid imagery. The group also expresses their pride in their roots, their culture, and their music. The album's tone is mostly aggressive and defiant, but also humorous and sarcastic at times.
- -The album was a huge success in Hungary, selling over 50,000 copies and earning a platinum certification. The album also received critical acclaim from both fans and critics, who praised the group's skills, originality, and authenticity. The album is widely regarded as one of the best Hungarian hip hop albums of all time, and it influenced many other artists in the genre.
- -In 2018, the group decided to re-release their classic album under their own label MFM Music. The re-release features the same 13 tracks as the original album, but with improved sound quality and a new cover art. The re-release also includes a bonus track called "Mexico Kid 50", which is a tribute to one of their former members who passed away in 2017.
- -The re-release was made to celebrate the 20th anniversary of the group's formation, and to introduce their music to a new generation of listeners. The re-release was well-received by both old and new fans, who appreciated the chance to revisit or discover one of the most important albums in Hungarian hip hop history.
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Is Hirens BootCD v13.4 legal and safe to use? | -Hirens BootCD v13.4 is legal and safe to use as long as you use it for legitimate purposes and do not violate any laws or ethical principles. However, some of the programs and utilities in Hirens BootCD v13.4 may be considered illegal or unsafe by some antivirus software or authorities, depending on how you use them. Therefore, you should use Hirens BootCD v13.4 at your own risk and discretion. | -
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WhatsApp is one of the most popular messaging apps in the world, but it is not officially supported on older iOS devices running iOS 4.2.1 or lower. However, there is a way to download and install WhatsApp on these devices using a patched IPA file that bypasses the compatibility check. In this article, we will show you how to do that step by step.
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An IPA file is an iOS application archive file that contains the app binary and other resources such as images, sounds, and fonts. You can install IPA files on your iOS device using iTunes or third-party tools such as Cydia Impactor or AltStore. However, you need to have a valid Apple ID and password to sign the IPA file before installing it.
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Juz 30 is the last part of the Quran, the holy book of Islam. It consists of 37 surahs (chapters), from Surah An-Naba (The News) to Surah An-Nas (The Mankind). It covers about 50 pages of the Quran and can be recited in less than an hour.
-Juz 30 is also known as Juz Amma, because it starts with the first word of Surah An-Naba, which is "Amma" (meaning "What"). It is also called Juz Tabarak, because it contains Surah Al-Mulk (The Sovereignty), which begins with "Tabarak" (meaning "Blessed").
-Juz 30 is the last part of the Quran that was revealed to Prophet Muhammad (peace be upon him) over a period of 23 years. It contains some of the earliest and some of the latest revelations. It summarizes the main themes and messages of the Quran, such as the oneness of God, the resurrection, the accountability, the guidance, the mercy, and the warning.
-Juz 30 contains many short and powerful surahs that are easy to memorize and recite. They are also very relevant and applicable to our daily lives. They teach us about our purpose in life, our relationship with God, our moral values, our social responsibilities, our spiritual aspirations, and our ultimate destiny.
-Some of the famous surahs in Juz 30 are Surah Al-Fatihah (The Opening), Surah Al-Ikhlas (The Sincerity), Surah Al-Falaq (The Daybreak), Surah An-Nas (The Mankind), Surah Al-Kafirun (The Disbelievers), Surah Al-Asr (The Time), Surah Al-Qadr (The Power), Surah Al-Zalzalah (The Earthquake), Surah Al-Bayyinah (The Clear Proof), Surah Al-Qariah (The Calamity), Surah Al-Duha (The Morning Brightness), Surah Al-Inshirah (The Expansion), Surah Al-Tin (The Fig), Surah Al-Alaq (The Clot), Surah Al-Qadr (The Power), Surah Al-Kawthar (The Abundance), Surah Al-Maun (The Small Kindnesses), Surah Al-Kafirun (The Disbelievers), Surah An-Nasr (The Help), and Surah Al-Masad (The Palm Fiber).
-Juz 30 helps Muslims to memorize and recite the Quran, which is one of the best acts of worship in Islam. The Prophet Muhammad (peace be upon him) said, "The best among you are among my people is the one who learns the Quran and teaches it."
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Therefore, you need to be careful and selective when choosing a website to download Juz 30 PDF from. Here are some tips to help you find a good website:
-A reliable and authentic website is one that has a good reputation and credibility among the Muslim community. It should also have a clear and transparent policy about its sources, methods, and objectives. It should not have any hidden agendas or ulterior motives that might affect the quality or integrity of the content.
-One way to check the reliability and authenticity of a website is to look for reviews, ratings, testimonials, or endorsements from other users or experts. You can also check the domain name, the design, the layout, the navigation, the contact information, and the terms and conditions of the website. A good website should have a professional and user-friendly appearance and functionality.
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-You should reflect on the meanings and messages of the surahs with attention, concentration, and respect. You should also reflect on them with an open mind, a humble heart, and a sincere intention. You should try to relate them to your personal experiences, situations, and challenges. You should also try to learn the lessons, morals, and advices of the surahs.
-In conclusion, Juz 30 is the last part of the Quran that contains many short and powerful surahs. It is important for Muslims to memorize and recite it, as well as to understand and implement it. To download Juz 30 PDF online, you need to use a reliable and authentic website, choose the translation and recitation you prefer, and download the PDF file to your device or cloud storage. To read and benefit from Juz 30 PDF, you need to open the PDF file with a good PDF reader, read the Arabic text and the translation, listen to the recitation and follow along, and reflect on the meanings and messages of the surahs. We hope this article has helped you to learn how to download Juz 30 PDF and enjoy its blessings.
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What is the best time to read Juz 30? | -The best time to read Juz 30 is whenever you have some free time and a calm mind. However, some recommended times are before or after the obligatory prayers, before going to bed, or during the night. | -
How can I memorize Juz 30 easily? | -Some tips to memorize Juz 30 easily are: repeat each surah several times until you master it, review the previous surahs regularly, recite along with a reciter or a teacher, use flashcards or apps to test yourself, and ask God for help and guidance. | -
How can I understand Juz 30 better? | -Some tips to understand Juz 30 better are: read different translations and interpretations of the surahs, listen to lectures or podcasts that explain the surahs, join a study circle or a class that teaches the surahs, and ask questions or seek clarifications from knowledgeable people. | -
How can I implement Juz 30 in my life? | -Some tips to implement Juz 30 in your life are: act upon the commands and prohibitions of the surahs, follow the examples and stories of the surahs, avoid the sins and evils of the surahs, seek the rewards and blessings of the surahs, and share the knowledge and wisdom of the surahs with others. | -
Where can I find more resources about Juz 30? | -Some websites that offer more resources about Juz 30 are: Quran.com, Quranexplorer.com, QuranicAudio.com, Tanzil.net, AlQuranic.com, QuranicPath.com, QuranStudyApp.com, QuranAcademy.io, QuranMajeed.app, and more. | -
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