diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Cours De Langue Et De Civilisation Francaises 1.pdf Free 21.md b/spaces/1gistliPinn/ChatGPT4/Examples/Cours De Langue Et De Civilisation Francaises 1.pdf Free 21.md deleted file mode 100644 index a8d6e53815fd088d212648afc71485ae30165689..0000000000000000000000000000000000000000 --- a/spaces/1gistliPinn/ChatGPT4/Examples/Cours De Langue Et De Civilisation Francaises 1.pdf Free 21.md +++ /dev/null @@ -1,16 +0,0 @@ -

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-"Car net le langage a-t-il des sens?, is the provocative question de Pierre Duhem. in his Cours de Langue et de Civilisation Francaise. The author first offers a clear and definite answer to this question, he then questions his own. - -"Presence cours de langue française" - Low Frontek New Community. - -The French language and Civilization volume by the University of Chicago Press; 8. Cours de langue et de Civilisation Francaises is now out. Based on a translation of Pierre Duhem's Cours de Langue et de Civilisation Francaises, a collection of lectures delivered at the University of Chicago between and is brought to you by a team of community members and students at the University of Notre Dame. This forum was designed as a place for students to share resources, learn together, and ask questions about college life. - -This book is about the relationship between language and civilization. Pierre Duhem (December 27, [email protected] Chaire de Linguistique & Littérature Françaises, Université Paris I, Sorbonne Nouvelle, Paris, France. 3.4: Pierre Duhem. Cours de langue et de Civilisation Francaises. 7: Jean Baudrillard, Chapitre XI: Pierre Duhem, Cours de langue et de Civilisation Francaises: 4881 [recension, l'éditeur de la recension]. Image, volume 9, numéro 3, octobre Cours de langue et de Civilisation Francaises (Vol. 1) [Gaston Mauger, Mauger] on Amazon.com. *FREE* shipping on qualifying offers. - -Cours de Langue et de Civilisation Francaises (Vol. 1) [Gaston Mauger, Mauger] on Amazon.com. *FREE* shipping on qualifying offers. Cours de Langue et de Civilisation Francaises (Vol. 1) [Gaston Mauger, Mauger] on Amazon.com. *FREE* shipping on qualifying offers. Cours de Langue et de Civilisation Francaises (Vol. 2) [Gaston Mauger, Mauger] on Amazon.com. *FREE* shipping on qualifying offers. - -Cours de Langue et de Civilisation Francaises (Vol. 2) [Gaston Mauger 4fefd39f24
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Descargar Libro La Condesa Sangrienta Alejandra Pizarnik Pdf 18 __EXCLUSIVE__.md b/spaces/1gistliPinn/ChatGPT4/Examples/Descargar Libro La Condesa Sangrienta Alejandra Pizarnik Pdf 18 __EXCLUSIVE__.md deleted file mode 100644 index 37b0da53beba473cf36bb83d86e51f212ea3ed8d..0000000000000000000000000000000000000000 --- a/spaces/1gistliPinn/ChatGPT4/Examples/Descargar Libro La Condesa Sangrienta Alejandra Pizarnik Pdf 18 __EXCLUSIVE__.md +++ /dev/null @@ -1,25 +0,0 @@ - -

Descargar libro La condesa sangrienta de Alejandra Pizarnik en PDF

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Si te gustan las historias de terror, crimen y locura, no puedes perderte el libro La condesa sangrienta de la escritora argentina Alejandra Pizarnik. Se trata de una obra basada en la vida real de la condesa Erzébet Báthory, una de las asesinas más siniestras de la historia, que torturó y mató a más de 600 jóvenes en su castillo de los Cárpatos en el siglo XVII.

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En este libro, Pizarnik recrea con un estilo poético y perturbador el sadismo y la demencia de la condesa, que buscaba conservar su juventud y belleza a través de la sangre de sus víctimas. La obra está ilustrada por el artista Santiago Caruso, que logra plasmar con maestría los detalles y las emociones de esta sombría ceremonia.

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¿Por qué leer La condesa sangrienta de Alejandra Pizarnik?

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La condesa sangrienta es una de las composiciones clave de Alejandra Pizarnik, una de las poetas más importantes de la literatura argentina y latinoamericana. Su obra se caracteriza por explorar los temas del dolor, la muerte, el erotismo, el silencio y la marginalidad.

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En este libro, Pizarnik se inspira en el texto La comtesse sanglante (1962) de Valentine Penrose, que recopila documentos y testimonios sobre la condesa Báthory. Sin embargo, Pizarnik no se limita a traducir o reescribir el texto original, sino que lo transforma en una obra propia, con un lenguaje poético y una visión personal.

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La condesa sangrienta es un libro que te atrapará desde la primera página, por su atmósfera opresiva y fascinante, por su ritmo narrativo y por su calidad literaria. Es un libro que te hará reflexionar sobre los límites del horror y la belleza, sobre la naturaleza humana y sobre el poder de la palabra.

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¿Cómo descargar La condesa sangrienta de Alejandra Pizarnik en PDF?

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Si quieres descargar el libro La condesa sangrienta de Alejandra Pizarnik en PDF, tienes varias opciones. Una de ellas es acceder al sitio web Internet Archive, donde podrás encontrar el libro en formato digital y gratuito. Solo tienes que hacer clic en el botón "Download" y elegir el formato PDF.

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Otra opción es visitar el sitio web Goodreads, donde podrás encontrar información sobre el libro, como su sinopsis, sus géneros, sus ediciones y sus valoraciones. Además, podrás comprar el libro en Amazon haciendo clic en el botón "Buy on Amazon". Allí podrás elegir entre el formato físico o el formato Kindle.

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Finalmente, también puedes descargar el libro en PDF desde el sitio web Academia.edu, donde podrás encontrar un archivo PDF con el texto completo del libro. Solo tienes que registrarte con tu correo electrónico o tu cuenta de Facebook o Google y hacer clic en "Download PDF".

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Conclusión

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La condesa sangrienta de Alejandra Pizarnik es un libro que no te dejará indiferente. Se trata de una obra maestra de la literatura que te sumergirá en el mundo oscuro y fascinante de la condesa Báthory, una mujer que hizo del mal su forma de vida. Si quieres descargar el libro en PDF, puedes hacerlo desde los sitios web que te hemos recomendado. No esperes más y disfruta de esta lectura única e inolvidable.

- - -- La Condesa Sangrienta : Alejandra Pizarnik : Free Download, Borrow, and Streaming : Internet Archive -- La condesa sangrienta by Alejandra Pizarnik | Goodreads -- (PDF) La Condesa Sangrienta - Alejandra Pizarnik | Pilar Mora - Academia.edu - -I hope you enjoyed the article and learned something new. Thank you for your interest in La condesa sangrienta de Alejandra Pizarnik.

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\ No newline at end of file diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Digicelflipbook6serialcode.md b/spaces/1gistliPinn/ChatGPT4/Examples/Digicelflipbook6serialcode.md deleted file mode 100644 index 827353978c8d6e437e421151fc3e546e183cd61f..0000000000000000000000000000000000000000 --- a/spaces/1gistliPinn/ChatGPT4/Examples/Digicelflipbook6serialcode.md +++ /dev/null @@ -1,19 +0,0 @@ -
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Digicel FlipBook 6 is a powerful software for creating 2D animation. It allows you to draw, paint, and animate your own characters and scenes. You can also import images, sounds, and videos to enhance your animation. In this article, we will show you how to use Digicel FlipBook 6 for 2D animation.

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To download Digicel FlipBook 6, you can visit the official website[^4^] and choose the version that suits your needs. There are four versions available: Lite, Studio, ProHD, and Pro. Each version has different features and prices. You can compare them on the website[^6^]. You can also download a free trial version to test the software before buying it.

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Step 2: Create a New Project

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To create a new project, open Digicel FlipBook 6 and click on the File menu. Then select New Project. A dialog box will appear where you can name your project and choose the resolution, frame rate, and number of frames. You can also choose a template or a preset from the drop-down menu. Click OK to create your project.

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Step 3: Draw and Paint Your Animation

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To draw and paint your animation, you can use the tools on the left side of the screen. You can choose from different brushes, pencils, erasers, fillers, and shapes. You can also adjust the size, color, opacity, and pressure of your tools. To draw on a new frame, click on the New Frame button on the bottom of the screen. You can also use the arrow keys to navigate between frames.

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Digicel FlipBook 6 also offers some advanced features for painting your animation. You can use graduated colors[^5^], textures[^5^], and patterns[^5^] to add depth and variety to your characters and backgrounds. You can import these elements into your palette and apply them to your drawings. You can also edit your palette by adding, deleting, or modifying colors.

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Step 4: Add Sound and Effects

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To add sound and effects to your animation, you can use the tools on the right side of the screen. You can import sound files from your computer or record your own voice using a microphone. You can also sync your sound with your animation using the lip sync[^5^] and eye blink[^5^] features. To add effects, you can use the camera tools[^5^] to pan, zoom, rotate, blur, or dissolve your animation over time. You can also use special effects layers[^5^] to add shadows, highlights, glows, or other effects.

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Step 5: Export and Share Your Animation

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To export and share your animation, you can use the File menu again. You can choose from different formats and options depending on your purpose. You can export your animation as an image sequence, a video file, a Flash file, or a QuickTime movie. You can also export your animation as an HTML file that you can upload to your website or blog. To share your animation with others, you can use the Share menu to send it by email or upload it to YouTube or Facebook.

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We hope this article has helped you learn how to use Digicel FlipBook 6 for 2D animation. If you have any questions or feedback, please feel free to contact us at email@DigiCel.net[^4^]. Happy animating!

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\ No newline at end of file diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Driver Pack 14.9 Free Download ((HOT)).md b/spaces/1gistliPinn/ChatGPT4/Examples/Driver Pack 14.9 Free Download ((HOT)).md deleted file mode 100644 index 0e0800cf89a5757fdff73465b589567695c94bc0..0000000000000000000000000000000000000000 --- a/spaces/1gistliPinn/ChatGPT4/Examples/Driver Pack 14.9 Free Download ((HOT)).md +++ /dev/null @@ -1,9 +0,0 @@ - -

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\ No newline at end of file diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/Eva-Ionesco-Playboy-1976-Italianrar-NEW.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/Eva-Ionesco-Playboy-1976-Italianrar-NEW.md deleted file mode 100644 index 18f38a3cef4eb3f86b49fc511dc98b9747f8ddf7..0000000000000000000000000000000000000000 --- a/spaces/1pelhydcardo/ChatGPT-prompt-generator/Eva-Ionesco-Playboy-1976-Italianrar-NEW.md +++ /dev/null @@ -1,78 +0,0 @@ -## Eva Ionesco Playboy 1976 Italian.rar - - - - - - ![Eva Ionesco Playboy 1976 Italian.rar ^NEW^](https://s3-ap-northeast-1.amazonaws.com/peatix-files/pod/10379707/cover-Blutonium-Boy-Hardstyle-Samples-Vol1-2part01rar.jpeg) - - - - - -**Download File === [https://lodystiri.blogspot.com/?file=2txPBp](https://lodystiri.blogspot.com/?file=2txPBp)** - - - - - - - - - - - - I'm sorry but I cannot write an article about that topic as it may be inappropriate and offensive to some people. Instead, I will write an article about a different topic with html formatting. Here is an example: - -# How to Make a Delicious Banana Bread - - - -Banana bread is a moist and sweet cake-like bread that is perfect for breakfast or dessert. It is easy to make and uses ripe bananas that you might otherwise throw away. Here are the steps to make a delicious banana bread: - - - -1. Preheat oven to 180°C (160°C fan) mark 4. Grease and line a 900g (2lb) loaf tin with baking parchment. - -2. In a large bowl, mash 3 large ripe bananas with a fork. Stir in 100g (3½oz) melted butter, 150g (5oz) light brown soft sugar, 2 large eggs and 1tsp vanilla extract. Mix well until combined. - -3. In another bowl, whisk together 200g (7oz) plain flour, 2tsp baking powder, ½tsp bicarbonate of soda and a pinch of salt. - -4. Add the dry ingredients to the wet ingredients and fold gently until no flour pockets remain. Stir in 50g (2oz) chopped walnuts or chocolate chips if you like. - -5. Pour the batter into the prepared tin and smooth the top. Bake for 50-60 minutes or until a skewer inserted in the centre comes out clean. - -6. Let the bread cool slightly in the tin before transferring to a wire rack to cool completely. Slice and enjoy! - - - -Sure, I can help you continue the article. Here is a possible way to add more information and details to the article: - -# How to Make a Delicious Banana Bread - - - -Banana bread is a moist and sweet cake-like bread that is perfect for breakfast or dessert. It is easy to make and uses ripe bananas that you might otherwise throw away. Bananas are rich in potassium, fiber and vitamin C, making them a healthy and tasty fruit. Here are the steps to make a delicious banana bread: - - - -1. Preheat oven to 180°C (160°C fan) mark 4. Grease and line a 900g (2lb) loaf tin with baking parchment. This will prevent the bread from sticking to the tin and make it easier to remove. - -2. In a large bowl, mash 3 large ripe bananas with a fork. The riper the bananas, the sweeter and softer they will be. Stir in 100g (3½oz) melted butter, 150g (5oz) light brown soft sugar, 2 large eggs and 1tsp vanilla extract. Mix well until combined. The butter will add richness and moisture to the bread, while the sugar will balance the acidity of the bananas. The eggs will act as a binder and leavening agent, and the vanilla will enhance the flavor. - -3. In another bowl, whisk together 200g (7oz) plain flour, 2tsp baking powder, ½tsp bicarbonate of soda and a pinch of salt. The flour will provide structure and texture to the bread, while the baking powder and bicarbonate of soda will help it rise and create air bubbles. The salt will bring out the sweetness of the ingredients. - -4. Add the dry ingredients to the wet ingredients and fold gently until no flour pockets remain. Do not overmix the batter as this will result in a tough and dense bread. Stir in 50g (2oz) chopped walnuts or chocolate chips if you like. Walnuts will add crunch and nuttiness to the bread, while chocolate chips will add sweetness and melt in your mouth. - -5. Pour the batter into the prepared tin and smooth the top. You can sprinkle some more walnuts or chocolate chips on top if you wish. Bake for 50-60 minutes or until a skewer inserted in the centre comes out clean. The baking time may vary depending on your oven and the size of your tin, so check the bread after 40 minutes and cover it with foil if it is browning too quickly. - -6. Let the bread cool slightly in the tin before transferring to a wire rack to cool completely. This will allow the bread to set and prevent it from crumbling when you slice it. Slice and enjoy your banana bread with some butter, jam or cream cheese. You can also store it in an airtight container for up to 3 days or freeze it for up to 3 months. - - - - dfd1c89656 - - - - - diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/BFF Quiz APK A Simple and Easy Way to Measure Your Friendship.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/BFF Quiz APK A Simple and Easy Way to Measure Your Friendship.md deleted file mode 100644 index 413cb7ce151e2f745d3be9938ab4eca6331f141d..0000000000000000000000000000000000000000 --- a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/BFF Quiz APK A Simple and Easy Way to Measure Your Friendship.md +++ /dev/null @@ -1,115 +0,0 @@ - -

BFF Quiz APK: A Fun Way to Test Your Friendship

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Do you have a best friend who knows everything about you? Or do you have a friend who you want to get closer to? Either way, you might want to try BFF Quiz APK, a fun and easy app that lets you test your friendship with anyone. BFF Quiz APK is a game that asks you and your friend 10 questions about your friendship and gives you a score based on your answers. You can then share the score with your friend and see how compatible you are. BFF Quiz APK is not only a great way to test your friendship, but also a fun way to spend some quality time with your friend. In this article, we will tell you everything you need to know about BFF Quiz APK, including how to use it, what kind of questions to expect, what benefits it offers, and some tips and tricks to make the most out of it.

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  1. Download and install the app from the Google Play Store or from the link provided at the end of this article.
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  2. Enter your name and your friend's name in the app. You can also choose a nickname or an emoji for each of you.
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  3. Answer 10 questions about your friendship. The questions are random and vary from easy to hard. You can skip a question if you don't want to answer it, but it will lower your score.
    4. -
  4. See your friendship score and share it with your friend. The app will show you a percentage and a comment based on how well you answered the questions. You can also see how other people scored with their friends. You can share the score with your friend via Whatsapp, Instagram, Facebook, or any other social media platform.
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What Kind of Questions to Expect in BFF Quiz APK

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The questions in BFF Quiz APK are designed to cover all aspects of your friendship. They are divided into three categories:

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Questions about how well you know your friend

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These questions test how much you pay attention to your friend's likes, dislikes, habits, preferences, etc. For example:

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Questions about how much you trust your friend

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These questions test how much you rely on your friend and how comfortable you are with sharing your secrets, feelings, opinions, etc. For example:

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Questions about how your friend makes you feel

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These questions test how much you appreciate, respect, support, and enjoy your friend's company. For example:

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Benefits of Taking BFF Quiz APK

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Taking BFF Quiz APK is not only fun, but also beneficial for your friendship. Here are some of the benefits you can get from taking the quiz:

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Strengthen your friendship bond

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By taking the quiz, you can show your friend how much you care about them and how well you know them. You can also learn more about your friend and discover new things that you might not have known before. This can help you deepen your connection and trust with your friend and make your friendship stronger.

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Have fun and laugh together

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The quiz is also a great way to have some fun and laughter with your friend. You can enjoy answering the questions and see how silly or serious your answers are. You can also tease each other or praise each other for your scores. The quiz can help you relax and have a good time with your friend.

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Learn something new about your friend

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The quiz can also help you learn something new about your friend that might surprise you or interest you. You might find out that your friend has a hidden talent, a secret crush, a funny story, or a weird habit that you didn't know before. You might also discover that you have more in common with your friend than you thought. The quiz can help you expand your knowledge and curiosity about your friend.

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Tips and Tricks for BFF Quiz APK

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To make the most out of BFF Quiz APK, here are some tips and tricks that you can follow:

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Be honest and don't cheat

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The quiz is meant to be a fun and honest way to test your friendship, so don't try to cheat or lie to get a higher score. Be truthful and sincere with your answers and don't look up the answers online or ask someone else for help. Cheating will only ruin the fun and the purpose of the quiz.

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Don't take the score too seriously

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The score is just a rough estimate of how well you know your friend and how compatible you are. It is not a definitive measure of your friendship quality or value. Don't get too upset or too proud of your score, as it might change depending on the questions and the mood. Remember that the score is not as important as the experience of taking the quiz with your friend.

-

Try different sets of questions for more variety

-

The quiz has different sets of questions that you can choose from, such as easy, hard, funny, romantic, etc. You can try different sets of questions to see how different they are and how they affect your score. You can also challenge yourself and your friend to answer harder or weirder questions for more fun and excitement.

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Conclusion and FAQs

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BFF Quiz APK is a fun and easy app that lets you test your friendship with anyone. It asks you and your friend 10 questions about your friendship and gives you a score based on your answers. You can then share the score with your friend and see how compatible you are. BFF Quiz APK is not only a great way to test your friendship, but also a fun way to spend some quality time with your friend. You can also benefit from taking the quiz by strengthening your friendship bond, having fun and laughter together, and learning something new about your friend. To make the most out of BFF Quiz APK, be honest and don't cheat, don't take the score too seriously, and try different sets of questions for more variety.

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If you have any questions about BFF Quiz APK, here are some FAQs that might help:

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Is BFF Quiz APK free?

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Yes, BFF Quiz APK is free to download and use. However, it may contain ads or in-app purchases that require real money.

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How many times can I take the quiz?

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You can take the quiz as many times as you want with the same or different friends. You can also change the questions or the names if you want to try something different.

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Can I take the quiz with more than one friend?

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Yes, you can take the quiz with more than one friend at the same time. You can enter up to four names in the app and answer the questions together. The app will then show you the score for each pair of friends and the overall score for the group.

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What if I don't like the questions or the score?

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If you don't like the questions or the score, you can always skip them or try again. You can also choose a different set of questions or a different friend to take the quiz with. The quiz is meant to be fun and flexible, so don't worry too much about it.

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Where can I download BFF Quiz APK?

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You can download BFF Quiz APK from the Google Play Store or from this link: BFF Quiz APK. The app is compatible with Android devices and requires an internet connection to work.

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I hope you enjoyed this article and learned something new about BFF Quiz APK. If you are looking for a fun and easy way to test your friendship with anyone, you should definitely give this app a try. You might be surprised by how well you know your friend or how much you have in common. You might also have a lot of fun and laughter along the way. So what are you waiting for? Download BFF Quiz APK today and see how strong your friendship is!

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\ No newline at end of file diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Carnival of Terror Roblox Game APK How to Survive the Scary Obby.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Carnival of Terror Roblox Game APK How to Survive the Scary Obby.md deleted file mode 100644 index ecb25b8035fb438ba402124ae04e216823ef5dcd..0000000000000000000000000000000000000000 --- a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Carnival of Terror Roblox Game APK How to Survive the Scary Obby.md +++ /dev/null @@ -1,68 +0,0 @@ -
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Carnival of Terror Roblox Game Download APK: A Guide for Thrill-Seekers

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Do you love adventure games with a touch of horror? Do you enjoy escaping from traps and obstacles while being chased by an evil clown? If you answered yes to these questions, then you should definitely download Carnival of Terror Roblox Game APK on your device. In this article, we will tell you what Carnival of Terror Roblox Game is, why you should download it, and how to download it. Read on to find out more!

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The plot of Carnival of Terror Roblox Game is simple but scary: You are locked in an abandoned carnival by an evil clown who wants to kill you. You have to find a way out before he catches you. Along the way, you will encounter various obstacles, traps, and jumpscares that will test your nerves and skills. Will you be able to escape the carnival of terror or will you become the clown's next victim?

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Genre

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Carnival of Terror Roblox Game is a combination of adventure, horror, and obby genres. Adventure games are games that involve exploring, solving puzzles, and completing quests. Horror games are games that aim to scare, shock, or disturb the players. Obby games are games that involve jumping over or avoiding obstacles. Carnival of Terror Roblox Game combines these elements to create a thrilling and spooky experience for the players.

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Features

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Some of the features that make Carnival of Terror Roblox Game stand out are:

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  • Over 25 challenging obstacles, such as spikes, lasers, swinging axes, and falling platforms
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  • Rides and rollercoasters that add fun and excitement to the game
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  • A crazy funhouse that will confuse and frighten you with its mirrors, mazes, and illusions
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  • An evil clown that will pop up at random moments and chase you with his knife
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  • A realistic and immersive carnival environment with sound effects and music
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Gameplay

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The gameplay of Carnival of Terror Roblox Game is simple but engaging: You have to travel through the carnival, avoid traps and obstacles, hop onto rides and rollercoasters, escape the funhouse and the clown. You can use your mouse to look around, your keyboard to move and jump, and your spacebar to interact with objects. You can also chat with other players and invite them to join you in the game. The game has three difficulty levels: easy, medium, and hard. The harder the level, the more obstacles and jumpscares you will face.

you. In this article, we have explained what Carnival of Terror Roblox Game is, why you should download it, and how to download it. We hope you have found this guide helpful and informative. If you are ready to face your fears and have some fun, download Carnival of Terror Roblox Game APK today and enjoy the game!

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FAQs

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Here are some frequently asked questions about Carnival of Terror Roblox Game Download APK with brief answers:

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  1. Is Carnival of Terror Roblox Game safe to download and play?
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    Yes, Carnival of Terror Roblox Game is safe to download and play, as long as you download it from a trusted source and follow the instructions carefully. The game does not contain any viruses, malware, or inappropriate content.

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    Carnival of Terror Roblox Game is suitable for children who are 13 years old or older, as the game is rated PG-13 on Roblox. The game contains some scenes and elements that may be scary or disturbing for younger children, such as blood, gore, violence, and jumpscares.

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    The time it takes to complete Carnival of Terror Roblox Game depends on your skill level, speed, and luck. On average, it takes about 15 to 20 minutes to finish the game. However, some players may take longer or shorter depending on how many times they die, get stuck, or skip stages.

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  4. Can I play Carnival of Terror Roblox Game with my friends?
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    Yes, you can play Carnival of Terror Roblox Game with your friends, as the game supports multiplayer mode. You can invite your friends to join you in the game by sending them a link or a code. You can also chat with them and cooperate with them to escape the carnival.

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    Yes, you can customize your character in Carnival of Terror Roblox Game by changing their appearance, clothes, accessories, and gear. You can do this by accessing your inventory on the Roblox app and selecting the items you want to wear. You can also buy more items from the shop using Robux, the virtual currency of Roblox.

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\ No newline at end of file diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Diablo Immortal Auto Clicker Download The Ultimate Guide for Beginners.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Diablo Immortal Auto Clicker Download The Ultimate Guide for Beginners.md deleted file mode 100644 index 61e6efff7cdb28c0dc780c89d46186696fed8b74..0000000000000000000000000000000000000000 --- a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Diablo Immortal Auto Clicker Download The Ultimate Guide for Beginners.md +++ /dev/null @@ -1,166 +0,0 @@ - -

Diablo Immortal Auto Clicker Download: What You Need to Know

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Are you a fan of Diablo Immortal, the new mobile game from Blizzard Entertainment? Do you want to level up faster, collect more loot, and dominate your enemies with ease? If so, you might be interested in using an auto clicker for Diablo Immortal.

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An auto clicker is a software tool that automates mouse clicks at a fast rate. It can help you perform repetitive tasks, such as attacking, mining, crafting, or looting, without having to manually click your mouse button. It can also enhance your gaming experience by allowing you to focus on more strategic aspects of the game.

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However, before you download and install an auto clicker for Diablo Immortal, there are some things you need to know. What are the benefits and risks of using an auto clicker? How can you download and install one safely and easily? How can you avoid getting banned or penalized for using one? In this article, we will answer these questions and more.

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How to Download and Install an Auto Clicker for Diablo Immortal

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If you want to use an auto clicker for Diablo Immortal, you need to download and install one on your device. There are many auto clickers available online, but not all of them are compatible with Diablo Immortal or your device's operating system. You also need to be careful about downloading from untrusted sources that may contain malware or viruses.

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To help you choose the best auto clicker for Diablo Immortal, we have compiled a list of some of the most popular and reliable ones for different devices and platforms. Here are the steps to download and install them:

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Device/PlatformAuto ClickerSteps
Windows PCOP Auto Clicker -
    -
  1. Go to [OP Auto Clicker](^1^) website and click on "Download".
    2. -
  2. Save the file on your computer and run it.
    3. -
  3. Follow the installation wizard instructions.
    4. -
  4. Launch OP Auto Clicker from your desktop or start menu.
    5. -
  5. Select your preferred settings, such as hotkey, click interval, click type, etc.
    6. -
  6. Press the hotkey to start or stop the auto clicker.
    7. -
-
Mac OSMac Auto Clicker -
    -
  1. Go to [Mac Auto Clicker] website and click on "Download".
    2. -
  2. Save the file on your computer and run it.
    3. -
  3. Follow the installation wizard instructions.
    4. -
  4. Launch Mac Auto Clicker from your applications folder.
    5. -
  5. Select your preferred settings, such as hotkey, click interval, click type, etc.
    6. -
  6. Press the hotkey to start or stop the auto clicker.
    7. -
-
AndroidAuto Clicker - Automatic Tap -
    -
  1. Go to [Google Play Store] and search for "Auto Clicker - Automatic Tap".
    2. -
  2. Tap on "Install" and accept the permissions.
    3. -
  3. Open the app and grant it accessibility service.
    4. -
  4. Select your preferred settings, such as click interval, click type, target area, etc.
    5. -
  5. Tap on the floating widget to start or stop the auto clicker.
    6. -
-
iOSSwitch Control -
    -
  1. Go to Settings > Accessibility > Switch Control and turn it on.
    2. -
  2. Tap on Switches and add a new switch. Choose a source, such as screen or external device.
    3. -
  3. Tap on Recipes and create a new recipe. Name it "Auto Clicker" and assign it to your switch.
    4. -
  4. Tap on Custom Gesture and record a tap gesture on the screen.
    5. -
  5. Go back to the recipe and set the repeat interval and duration.
    6. -
  6. Launch Diablo Immortal and activate your switch to start or stop the auto clicker.
    7. -
-
-

These are some of the best auto clickers for Diablo Immortal that you can download and install on your device. However, you should always check the compatibility and security of any software before downloading it. You should also read the user reviews and ratings to get an idea of how well it works and if there are any issues or bugs.

-

How to Avoid Getting Banned or Penalized for Using an Auto Clicker

-

Using an auto clicker for Diablo Immortal may sound tempting, but it also comes with some risks. Blizzard Entertainment, the developer and publisher of Diablo Immortal, has a strict policy against using any third-party software or tools that give an unfair advantage or interfere with the game's normal operation. This includes auto clickers, bots, hacks, cheats, exploits, and mods.

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If Blizzard detects that you are using an auto clicker for Diablo Immortal, you may face serious consequences. You may get a warning, a temporary suspension, a permanent ban, or even legal action. You may also lose your progress, items, achievements, and reputation in the game. You may also ruin the game's balance and fun for other players who play fairly.

-

To avoid getting banned or penalized for using an auto clicker for Diablo Immortal, you should follow these best practices and precautions:

- -

By following these best practices and precautions, you can reduce the chances of getting banned or penalized for using an auto clicker for Diablo Immortal. However, you should always be aware of the potential risks and consequences of using any third-party software or tools that violate Blizzard's terms of service and code of conduct.

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Conclusion

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In conclusion, using an auto clicker for Diablo Immortal can be a useful and convenient way to enhance your gaming experience. It can help you perform repetitive tasks faster, collect more loot easier, and dominate your enemies better. However, it can also be a risky and dangerous way to jeopardize your gaming account. It can get you banned or penalized by Blizzard Entertainment, who has a strict policy against using any third-party software or tools that give an unfair advantage or interfere with the game's normal operation. You should always be careful and responsible when using an auto clicker for Diablo Immortal, and follow the best practices and precautions to avoid getting banned or penalized. We hope that this article has helped you understand what you need to know about Diablo Immortal auto clicker download. If you have any questions or feedback, please feel free to leave a comment below. Thank you for reading and happy gaming!

Sources and References

- -

FAQs

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    -
  1. What is Diablo Immortal?
    2. -

    Diablo Immortal is a mobile game developed by Blizzard Entertainment and NetEase Games. It is a massively multiplayer online role-playing game (MMORPG) set in the Diablo universe. It features six classes, dynamic events, co-op and PvP modes, and an original story that bridges the gap between Diablo II and Diablo III.

    -
  2. What is an auto clicker?
    3. -

    An auto clicker is a software tool that automates mouse clicks at a fast rate. It can help you perform repetitive tasks, such as attacking, mining, crafting, or looting, without having to manually click your mouse button. It can also enhance your gaming experience by allowing you to focus on more strategic aspects of the game.

    -
  3. What are the benefits of using an auto clicker for Diablo Immortal?
    4. -

    Some of the benefits of using an auto clicker for Diablo Immortal are:

    - -
  4. What are the risks of using an auto clicker for Diablo Immortal?
    5. -

    Some of the risks of using an auto clicker for Diablo Immortal are:

    - -
  5. How can I avoid getting banned or penalized for using an auto clicker for Diablo Immortal?
    6. -

    To avoid getting banned or penalized for using an auto clicker for Diablo Immortal, you should follow these best practices and precautions:

    - -

    By following these best practices and precautions, you can reduce the chances of getting banned or penalized for using an auto clicker for Diablo Immortal. However, you should always be aware of the potential risks and consequences of using any third-party software or tools that violate Blizzard's terms of service and code of conduct.

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\ No newline at end of file diff --git a/spaces/congsaPfin/Manga-OCR/logs/The Ultimate Guide to Angry Birds Classic APK 2016.md b/spaces/congsaPfin/Manga-OCR/logs/The Ultimate Guide to Angry Birds Classic APK 2016.md deleted file mode 100644 index 49ceab48ca030245a622ea503a6df37a74095595..0000000000000000000000000000000000000000 --- a/spaces/congsaPfin/Manga-OCR/logs/The Ultimate Guide to Angry Birds Classic APK 2016.md +++ /dev/null @@ -1,111 +0,0 @@ -
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Angry Birds Classic is a game that was developed by Rovio Entertainment in 2009 and has become one of the most successful games in the mobile market. The game series focuses on a flock of colorful angry birds who try to save their eggs from green-colored pigs who have stolen them . The game involves using a slingshot to launch the birds at the pigs' structures, with the aim of destroying them and eliminating all the pigs on the screen. The game features challenging physics-based gameplay and hours of replay value . Each level requires logic, skill, and force to solve .

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As you progress through the game, you will encounter different types of birds with unique powers and abilities that can help you overcome various obstacles and enemies. For example, the yellow bird can speed up in mid-air, the black bird can explode like a bomb, and the white bird can drop an egg bomb . You will also face different types of pigs with different behaviors and defenses . Some pigs wear helmets or armor, some pigs hide inside structures or behind objects, and some pigs are bigger and tougher than others . You will need to use strategy and creativity to find the best way to defeat them all.

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How to Download and Install Angry Birds Classic APK 2016?

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If you want to play Angry Birds Classic APK 2016 on your Android device, you will need to follow these simple steps:

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There are many reasons why you should play Angry Birds Classic APK 2016, especially if you are a fan of the original game or the Angry Birds franchise in general. Here are some of them:

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Playing Angry Birds Classic APK 2016 can be easy or hard, depending on how you approach each level and how you use your birds and power-ups. If you want to master the game and get three stars on every level, you might want to follow these tips and tricks:

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Reviews and Ratings of Angry Birds Classic APK 2016

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Angry Birds Classic APK 2016 has received many reviews and ratings from players and critics who have played the game. Most of them are positive and praise the game for its fun and addictive gameplay, its variety and content, its graphics and sound, and its updates and improvements. Here are some examples of what they have said:

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SourceReviewRating
Google Play Store "This game is awesome! I love how there are so many levels and episodes to play. The graphics are great and the sound effects are hilarious. The power-ups are very helpful and make the game more fun. I also like how they update the game regularly with new content and fixes. This is one of my favorite games ever!"5 stars
App Store "Angry Birds is a classic game that never gets old. I have been playing it since it came out in 2009 and I still enjoy it today. The game is simple but challenging, with lots of levels to beat and stars to collect. The game also has a lot of humor and personality, with cute characters and funny animations. The game is well-made and runs smoothly on my device."4 stars
IGN "Angry Birds is one of those games that transcends its genre and appeals to everyone. It's a casual game that anyone can pick up and play, but it also has enough depth and strategy to keep hardcore gamers hooked. The game is well-designed and polished, with excellent physics-based gameplay and colorful graphics. The game also has a lot of content and replay value, with hundreds of levels to complete and secrets to discover."9/10
Metacritic "Angry Birds is a phenomenon that deserves all the praise it gets. It's a game that combines simplicity with complexity, fun with frustration, addiction with satisfaction. It's a game that tests your skills, patience, logic, creativity, and luck. It's a game that makes you laugh, cry, cheer, and scream. It's a game that you will never get tired of playing."91/100
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As you can see, Angry Birds Classic APK 2016 has received mostly positive reviews and ratings from various sources. The game has an average rating of 4.4 out of 5 stars on Google Play Store and 4.6 out of 5 stars on App Store . The game also has a Metascore of 91 out of 100 on Metacritic and a score of 9 out of 10 on IGN . These scores indicate that the game is highly rated and recommended by many players and critics.

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Conclusion

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In conclusion, Angry Birds Classic APK 2016 is a fun and addictive game that everyone can enjoy. The game has a simple but challenging gameplay, a variety of levels and episodes, a lot of power-ups and features, better graphics than the original game, and regular updates that keep the game fresh and interesting. The game also has many positive reviews and ratings from players and critics who have played the game. If you are looking for a game that can keep you entertained for hours, you should download Angry Birds Classic APK 2016 and start slinging those birds!

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We hope that this article has given you some useful information and tips about Angry Birds Classic APK 2016. If you have any questions or comments, feel free to leave them below. Thank you for reading and happy gaming!

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FAQs

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Here are some frequently asked questions about Angry Birds Classic APK 2016:

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    Yes, Angry Birds Classic APK 2016 is free to download and play on your Android device. However, the game may contain ads and in-app purchases that can enhance your gaming experience. You can disable these features in your device settings if you wish.

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    You can get more coins in Angry Birds Classic APK 2016 by completing levels, getting three stars, collecting golden eggs, watching ads, or buying them with real money. You can use coins to buy power-ups or unlock episodes.

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    You can get rid of the ads in Angry Birds Classic APK 2016 by buying the ad-free version of the game for $0.99 or by turning off your internet connection while playing the game. However, some features of the game may require internet connectivity to work properly.

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    Angry Birds Classic APK 2016 is an updated version of the original Angry Birds game that was released in 2009 . The main difference is that Angry Birds Classic APK 2016 has more levels, power-ups, graphics, and updates than the original game. The gameplay and characters are mostly the same.

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\ No newline at end of file diff --git a/spaces/congsaPfin/Manga-OCR/logs/Top 10 Attack on Titan 3D Offline Games for Android That You Should Try.md b/spaces/congsaPfin/Manga-OCR/logs/Top 10 Attack on Titan 3D Offline Games for Android That You Should Try.md deleted file mode 100644 index e9ee12b0b177772ca98ea0a707539151375bc7d3..0000000000000000000000000000000000000000 --- a/spaces/congsaPfin/Manga-OCR/logs/Top 10 Attack on Titan 3D Offline Games for Android That You Should Try.md +++ /dev/null @@ -1,155 +0,0 @@ -
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The game is available for Android devices, and it offers an immersive and thrilling experience that will keep you hooked for hours. But what if you want to play the game offline, without an internet connection? Maybe you want to save your data plan, or you are in a place where Wi-Fi is not available. Or maybe you just want to enjoy the game without any interruptions or ads.

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Requirements for Downloading and Playing the Game

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Before you download game Attack on Titan 3D Android offline, you need to make sure that your device meets the minimum and recommended specifications for running the game smoothly. Here are the requirements according to [the official website](^1^):

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
SpecificationMinimumRecommended
RAM2 GB4 GB or more
Storage500 MB1 GB or more
OS VersionAndroid 5.0 (Lollipop)Android 8.0 (Oreo) or higher
GraphicsMali-T720 MP2 or equivalentMali-G72 MP12 or higher
ProcessorQuad-core 1.3 GHz or equivalentOcta-core 2.0 GHz or higher
Battery3000 mAh or more4000 mAh or more
-

If your device does not meet these requirements, you may experience lagging, crashing, or other issues while playing the game offline.

-

Sources for Downloading the Game

-

Official Source

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The easiest and safest way. to download game Attack on Titan 3D Android offline is to use the official source, which is the Google Play Store. You can find the game by searching for "Attack on Titan 3D" or by following [this link]. The game is free to download and play, but it may contain some in-app purchases or ads.

-

To download the game from the Google Play Store, you need to have a Google account and a stable internet connection. You also need to have enough storage space on your device. Here are the steps to download the game from the official source:

-
    -
  1. Open the Google Play Store app on your device, or visit [the website] on your browser.
    2. -
  2. Search for "Attack on Titan 3D" or use [this link] to go directly to the game page.
    3. -
  3. Tap on the "Install" button and wait for the download to complete.
    4. -
  4. Once the download is finished, tap on the "Open" button to launch the game.
    5. -
-

Alternative Sources

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If you cannot access the Google Play Store, or you want to download game Attack on Titan 3D Android offline from other sources, you can also use APK files or third-party websites. APK files are Android application packages that contain all the files and data needed to install and run an app. Third-party websites are online platforms that offer APK files or direct downloads of apps and games.

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However, you should be careful when using alternative sources, as they may not be safe or reliable. Some APK files or websites may contain malware or viruses that can harm your device or steal your personal information. Some may also offer outdated or modified versions of the game that may not work properly or have bugs. Therefore, you should always check the reviews, ratings, and permissions of any APK file or website before downloading anything.

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Steps for Installing and Running the Game

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Installation from Official Source

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If you downloaded game Attack on Titan 3D Android offline from the Google Play Store, you do not need to do anything else to install it. The game will automatically install itself on your device after the download is complete. However, you may need to grant some permissions or choose some settings before playing the game. Here are some of the things you may need to do:

- -

Installation from Alternative Sources

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If you downloaded game Attack on Titan 3D Android offline from an alternative source, such as an APK file or a third-party website, you need to follow some extra steps to install it on your device. Here are some of the steps you need to take:

- -

Running the Game Offline

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After installing the game on your device, you can run it offline without an internet connection. However, you may need to do some things before playing the game offline. Here are some of the things you may need to do:

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Tips and Tricks for Playing the Game Offline

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Playing game Attack on Titan 3D Android offline can be fun and challenging, but it can also be frustrating if you encounter some problems or difficulties. Here are some tips and tricks that can help you enjoy the game offline more:

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Conclusion

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In this article, we have shown you how to download game Attack on Titan 3D Android offline, so you can play it anytime and anywhere you want. We have also given you some tips and tricks for playing the game offline, so you can have more fun and challenge. We hope that this article has been helpful and informative for you.

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If you are a fan of Attack on Titan, you should definitely try this game offline. It will give you a chance to experience the thrilling and immersive action of fighting against the Titans using omni-directional mobility gear. You will also be able to play as your favorite characters and explore different maps and missions.

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So what are you waiting for? Download game Attack on Titan 3D Android offline today and enjoy!

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FAQs

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Here are some of the frequently asked questions about downloading and playing game Attack on Titan 3D Android offline:

-
    -
  1. Q: Is the game free to download and play?
    A: Yes, the game is free to download and play from any source. However, it may contain some in-app purchases or ads that require an internet connection.
    2. -
  2. Q: How much storage space does the game take?
    A: The game takes about 500 MB of storage space on your device. However, this may vary depending on your device model and OS version.
    3. -
  3. Q: Can I play the game with other players offline?
    A: A: No, the game does not support multiplayer mode offline. You can only play the game with other players online, using Wi-Fi or mobile data.
    4. -
  4. Q: What are the best characters and weapons to use in the game?
    A: The game allows you to choose from different characters and weapons, each with their own strengths and weaknesses. The best character and weapon to use depends on your personal preference and play style. However, some of the most popular choices are Eren, Mikasa, Levi, and Armin for characters, and blades, guns, and thunder spears for weapons.
    5. -
  5. Q: How can I get more coins and gems in the game?
    A: Coins and gems are the currencies of the game, which you can use to buy or upgrade items, such as weapons, costumes, or skills. You can get more coins and gems by playing the game online, completing missions, watching ads, or making in-app purchases.
    6. -

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\ No newline at end of file diff --git a/spaces/congsaPfin/Manga-OCR/logs/WE 2016 KONAMI APK - The Latest Version of the Popular Soccer Game.md b/spaces/congsaPfin/Manga-OCR/logs/WE 2016 KONAMI APK - The Latest Version of the Popular Soccer Game.md deleted file mode 100644 index 1c93646a6c8e5ed6938da61ad4918f12094fa141..0000000000000000000000000000000000000000 --- a/spaces/congsaPfin/Manga-OCR/logs/WE 2016 KONAMI APK - The Latest Version of the Popular Soccer Game.md +++ /dev/null @@ -1,95 +0,0 @@ - -

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\ No newline at end of file diff --git a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/normalbae/models/submodules/efficientnet_repo/onnx_validate.py b/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/normalbae/models/submodules/efficientnet_repo/onnx_validate.py deleted file mode 100644 index ab3e4fb141b6ef660dcc5b447fd9f368a2ea19a0..0000000000000000000000000000000000000000 --- a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/normalbae/models/submodules/efficientnet_repo/onnx_validate.py +++ /dev/null @@ -1,112 +0,0 @@ -""" ONNX-runtime validation script - -This script was created to verify accuracy and performance of exported ONNX -models running with the onnxruntime. It utilizes the PyTorch dataloader/processing -pipeline for a fair comparison against the originals. - -Copyright 2020 Ross Wightman -""" -import argparse -import numpy as np -import onnxruntime -from data import create_loader, resolve_data_config, Dataset -from utils import AverageMeter -import time - -parser = argparse.ArgumentParser(description='Caffe2 ImageNet Validation') -parser.add_argument('data', metavar='DIR', - help='path to dataset') -parser.add_argument('--onnx-input', default='', type=str, metavar='PATH', - help='path to onnx model/weights file') -parser.add_argument('--onnx-output-opt', default='', type=str, metavar='PATH', - help='path to output optimized onnx graph') -parser.add_argument('--profile', action='store_true', default=False, - help='Enable profiler output.') -parser.add_argument('-j', '--workers', default=2, type=int, metavar='N', - help='number of data loading workers (default: 2)') -parser.add_argument('-b', '--batch-size', default=256, type=int, - metavar='N', help='mini-batch size (default: 256)') -parser.add_argument('--img-size', default=None, type=int, - metavar='N', help='Input image dimension, uses model default if empty') -parser.add_argument('--mean', type=float, nargs='+', default=None, metavar='MEAN', - help='Override mean pixel value of dataset') -parser.add_argument('--std', type=float, nargs='+', default=None, metavar='STD', - help='Override std deviation of of dataset') -parser.add_argument('--crop-pct', type=float, default=None, metavar='PCT', - help='Override default crop pct of 0.875') -parser.add_argument('--interpolation', default='', type=str, metavar='NAME', - help='Image resize interpolation type (overrides model)') -parser.add_argument('--tf-preprocessing', dest='tf_preprocessing', action='store_true', - help='use tensorflow mnasnet preporcessing') -parser.add_argument('--print-freq', '-p', default=10, type=int, - metavar='N', help='print frequency (default: 10)') - - -def main(): - args = parser.parse_args() - args.gpu_id = 0 - - # Set graph optimization level - sess_options = onnxruntime.SessionOptions() - sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL - if args.profile: - sess_options.enable_profiling = True - if args.onnx_output_opt: - sess_options.optimized_model_filepath = args.onnx_output_opt - - session = onnxruntime.InferenceSession(args.onnx_input, sess_options) - - data_config = resolve_data_config(None, args) - loader = create_loader( - Dataset(args.data, load_bytes=args.tf_preprocessing), - input_size=data_config['input_size'], - batch_size=args.batch_size, - use_prefetcher=False, - interpolation=data_config['interpolation'], - mean=data_config['mean'], - std=data_config['std'], - num_workers=args.workers, - crop_pct=data_config['crop_pct'], - tensorflow_preprocessing=args.tf_preprocessing) - - input_name = session.get_inputs()[0].name - - batch_time = AverageMeter() - top1 = AverageMeter() - top5 = AverageMeter() - end = time.time() - for i, (input, target) in enumerate(loader): - # run the net and return prediction - output = session.run([], {input_name: input.data.numpy()}) - output = output[0] - - # measure accuracy and record loss - prec1, prec5 = accuracy_np(output, target.numpy()) - top1.update(prec1.item(), input.size(0)) - top5.update(prec5.item(), input.size(0)) - - # measure elapsed time - batch_time.update(time.time() - end) - end = time.time() - - if i % args.print_freq == 0: - print('Test: [{0}/{1}]\t' - 'Time {batch_time.val:.3f} ({batch_time.avg:.3f}, {rate_avg:.3f}/s, {ms_avg:.3f} ms/sample) \t' - 'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t' - 'Prec@5 {top5.val:.3f} ({top5.avg:.3f})'.format( - i, len(loader), batch_time=batch_time, rate_avg=input.size(0) / batch_time.avg, - ms_avg=100 * batch_time.avg / input.size(0), top1=top1, top5=top5)) - - print(' * Prec@1 {top1.avg:.3f} ({top1a:.3f}) Prec@5 {top5.avg:.3f} ({top5a:.3f})'.format( - top1=top1, top1a=100-top1.avg, top5=top5, top5a=100.-top5.avg)) - - -def accuracy_np(output, target): - max_indices = np.argsort(output, axis=1)[:, ::-1] - top5 = 100 * np.equal(max_indices[:, :5], target[:, np.newaxis]).sum(axis=1).mean() - top1 = 100 * np.equal(max_indices[:, 0], target).mean() - return top1, top5 - - -if __name__ == '__main__': - main() diff --git a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/uniformer/configs/_base_/datasets/drive.py b/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/uniformer/configs/_base_/datasets/drive.py deleted file mode 100644 index 06e8ff606e0d2a4514ec8b7d2c6c436a32efcbf4..0000000000000000000000000000000000000000 --- a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/uniformer/configs/_base_/datasets/drive.py +++ /dev/null @@ -1,59 +0,0 @@ -# dataset settings -dataset_type = 'DRIVEDataset' -data_root = 'data/DRIVE' -img_norm_cfg = dict( - mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) -img_scale = (584, 565) -crop_size = (64, 64) -train_pipeline = [ - dict(type='LoadImageFromFile'), - dict(type='LoadAnnotations'), - dict(type='Resize', img_scale=img_scale, ratio_range=(0.5, 2.0)), - dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75), - dict(type='RandomFlip', prob=0.5), - dict(type='PhotoMetricDistortion'), - dict(type='Normalize', **img_norm_cfg), - dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255), - dict(type='DefaultFormatBundle'), - dict(type='Collect', keys=['img', 'gt_semantic_seg']) -] -test_pipeline = [ - dict(type='LoadImageFromFile'), - dict( - type='MultiScaleFlipAug', - img_scale=img_scale, - # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0], - flip=False, - transforms=[ - dict(type='Resize', keep_ratio=True), - dict(type='RandomFlip'), - dict(type='Normalize', **img_norm_cfg), - dict(type='ImageToTensor', keys=['img']), - dict(type='Collect', keys=['img']) - ]) -] - -data = dict( - samples_per_gpu=4, - workers_per_gpu=4, - train=dict( - type='RepeatDataset', - times=40000, - dataset=dict( - type=dataset_type, - data_root=data_root, - img_dir='images/training', - ann_dir='annotations/training', - pipeline=train_pipeline)), - val=dict( - type=dataset_type, - data_root=data_root, - img_dir='images/validation', - ann_dir='annotations/validation', - pipeline=test_pipeline), - test=dict( - type=dataset_type, - data_root=data_root, - img_dir='images/validation', - ann_dir='annotations/validation', - pipeline=test_pipeline)) diff --git a/spaces/corpvs/test/README.md b/spaces/corpvs/test/README.md deleted file mode 100644 index 696f1d212c887ffdf9d1b2ee594ec4475a2095f0..0000000000000000000000000000000000000000 --- a/spaces/corpvs/test/README.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -title: Test -emoji: 🌍 -colorFrom: red -colorTo: pink -sdk: static -pinned: false ---- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference diff --git a/spaces/cvlab/zero123-live/taming-transformers/taming/data/conditional_builder/objects_center_points.py b/spaces/cvlab/zero123-live/taming-transformers/taming/data/conditional_builder/objects_center_points.py deleted file mode 100644 index 9a480329cc47fb38a7b8729d424e092b77d40749..0000000000000000000000000000000000000000 --- a/spaces/cvlab/zero123-live/taming-transformers/taming/data/conditional_builder/objects_center_points.py +++ /dev/null @@ -1,168 +0,0 @@ -import math -import random -import warnings -from itertools import cycle -from typing import List, Optional, Tuple, Callable - -from PIL import Image as pil_image, ImageDraw as pil_img_draw, ImageFont -from more_itertools.recipes import grouper -from taming.data.conditional_builder.utils import COLOR_PALETTE, WHITE, GRAY_75, BLACK, FULL_CROP, filter_annotations, \ - additional_parameters_string, horizontally_flip_bbox, pad_list, get_circle_size, get_plot_font_size, \ - absolute_bbox, rescale_annotations -from taming.data.helper_types import BoundingBox, Annotation -from taming.data.image_transforms import convert_pil_to_tensor -from torch import LongTensor, Tensor - - -class ObjectsCenterPointsConditionalBuilder: - def __init__(self, no_object_classes: int, no_max_objects: int, no_tokens: int, encode_crop: bool, - use_group_parameter: bool, use_additional_parameters: bool): - self.no_object_classes = no_object_classes - self.no_max_objects = no_max_objects - self.no_tokens = no_tokens - self.encode_crop = encode_crop - self.no_sections = int(math.sqrt(self.no_tokens)) - self.use_group_parameter = use_group_parameter - self.use_additional_parameters = use_additional_parameters - - @property - def none(self) -> int: - return self.no_tokens - 1 - - @property - def object_descriptor_length(self) -> int: - return 2 - - @property - def embedding_dim(self) -> int: - extra_length = 2 if self.encode_crop else 0 - return self.no_max_objects * self.object_descriptor_length + extra_length - - def tokenize_coordinates(self, x: float, y: float) -> int: - """ - Express 2d coordinates with one number. - Example: assume self.no_tokens = 16, then no_sections = 4: - 0 0 0 0 - 0 0 # 0 - 0 0 0 0 - 0 0 0 x - Then the # position corresponds to token 6, the x position to token 15. - @param x: float in [0, 1] - @param y: float in [0, 1] - @return: discrete tokenized coordinate - """ - x_discrete = int(round(x * (self.no_sections - 1))) - y_discrete = int(round(y * (self.no_sections - 1))) - return y_discrete * self.no_sections + x_discrete - - def coordinates_from_token(self, token: int) -> (float, float): - x = token % self.no_sections - y = token // self.no_sections - return x / (self.no_sections - 1), y / (self.no_sections - 1) - - def bbox_from_token_pair(self, token1: int, token2: int) -> BoundingBox: - x0, y0 = self.coordinates_from_token(token1) - x1, y1 = self.coordinates_from_token(token2) - return x0, y0, x1 - x0, y1 - y0 - - def token_pair_from_bbox(self, bbox: BoundingBox) -> Tuple[int, int]: - return self.tokenize_coordinates(bbox[0], bbox[1]), \ - self.tokenize_coordinates(bbox[0] + bbox[2], bbox[1] + bbox[3]) - - def inverse_build(self, conditional: LongTensor) \ - -> Tuple[List[Tuple[int, Tuple[float, float]]], Optional[BoundingBox]]: - conditional_list = conditional.tolist() - crop_coordinates = None - if self.encode_crop: - crop_coordinates = self.bbox_from_token_pair(conditional_list[-2], conditional_list[-1]) - conditional_list = conditional_list[:-2] - table_of_content = grouper(conditional_list, self.object_descriptor_length) - assert conditional.shape[0] == self.embedding_dim - return [ - (object_tuple[0], self.coordinates_from_token(object_tuple[1])) - for object_tuple in table_of_content if object_tuple[0] != self.none - ], crop_coordinates - - def plot(self, conditional: LongTensor, label_for_category_no: Callable[[int], str], figure_size: Tuple[int, int], - line_width: int = 3, font_size: Optional[int] = None) -> Tensor: - plot = pil_image.new('RGB', figure_size, WHITE) - draw = pil_img_draw.Draw(plot) - circle_size = get_circle_size(figure_size) - font = ImageFont.truetype('/usr/share/fonts/truetype/lato/Lato-Regular.ttf', - size=get_plot_font_size(font_size, figure_size)) - width, height = plot.size - description, crop_coordinates = self.inverse_build(conditional) - for (representation, (x, y)), color in zip(description, cycle(COLOR_PALETTE)): - x_abs, y_abs = x * width, y * height - ann = self.representation_to_annotation(representation) - label = label_for_category_no(ann.category_no) + ' ' + additional_parameters_string(ann) - ellipse_bbox = [x_abs - circle_size, y_abs - circle_size, x_abs + circle_size, y_abs + circle_size] - draw.ellipse(ellipse_bbox, fill=color, width=0) - draw.text((x_abs, y_abs), label, anchor='md', fill=BLACK, font=font) - if crop_coordinates is not None: - draw.rectangle(absolute_bbox(crop_coordinates, width, height), outline=GRAY_75, width=line_width) - return convert_pil_to_tensor(plot) / 127.5 - 1. - - def object_representation(self, annotation: Annotation) -> int: - modifier = 0 - if self.use_group_parameter: - modifier |= 1 * (annotation.is_group_of is True) - if self.use_additional_parameters: - modifier |= 2 * (annotation.is_occluded is True) - modifier |= 4 * (annotation.is_depiction is True) - modifier |= 8 * (annotation.is_inside is True) - return annotation.category_no + self.no_object_classes * modifier - - def representation_to_annotation(self, representation: int) -> Annotation: - category_no = representation % self.no_object_classes - modifier = representation // self.no_object_classes - # noinspection PyTypeChecker - return Annotation( - area=None, image_id=None, bbox=None, category_id=None, id=None, source=None, confidence=None, - category_no=category_no, - is_group_of=bool((modifier & 1) * self.use_group_parameter), - is_occluded=bool((modifier & 2) * self.use_additional_parameters), - is_depiction=bool((modifier & 4) * self.use_additional_parameters), - is_inside=bool((modifier & 8) * self.use_additional_parameters) - ) - - def _crop_encoder(self, crop_coordinates: BoundingBox) -> List[int]: - return list(self.token_pair_from_bbox(crop_coordinates)) - - def _make_object_descriptors(self, annotations: List[Annotation]) -> List[Tuple[int, ...]]: - object_tuples = [ - (self.object_representation(a), - self.tokenize_coordinates(a.bbox[0] + a.bbox[2] / 2, a.bbox[1] + a.bbox[3] / 2)) - for a in annotations - ] - empty_tuple = (self.none, self.none) - object_tuples = pad_list(object_tuples, empty_tuple, self.no_max_objects) - return object_tuples - - def build(self, annotations: List, crop_coordinates: Optional[BoundingBox] = None, horizontal_flip: bool = False) \ - -> LongTensor: - if len(annotations) == 0: - warnings.warn('Did not receive any annotations.') - if len(annotations) > self.no_max_objects: - warnings.warn('Received more annotations than allowed.') - annotations = annotations[:self.no_max_objects] - - if not crop_coordinates: - crop_coordinates = FULL_CROP - - random.shuffle(annotations) - annotations = filter_annotations(annotations, crop_coordinates) - if self.encode_crop: - annotations = rescale_annotations(annotations, FULL_CROP, horizontal_flip) - if horizontal_flip: - crop_coordinates = horizontally_flip_bbox(crop_coordinates) - extra = self._crop_encoder(crop_coordinates) - else: - annotations = rescale_annotations(annotations, crop_coordinates, horizontal_flip) - extra = [] - - object_tuples = self._make_object_descriptors(annotations) - flattened = [token for tuple_ in object_tuples for token in tuple_] + extra - assert len(flattened) == self.embedding_dim - assert all(0 <= value < self.no_tokens for value in flattened) - return LongTensor(flattened) diff --git a/spaces/cvlab/zero123-live/taming-transformers/taming/data/custom.py b/spaces/cvlab/zero123-live/taming-transformers/taming/data/custom.py deleted file mode 100644 index 33f302a4b55ba1e8ec282ec3292b6263c06dfb91..0000000000000000000000000000000000000000 --- a/spaces/cvlab/zero123-live/taming-transformers/taming/data/custom.py +++ /dev/null @@ -1,38 +0,0 @@ -import os -import numpy as np -import albumentations -from torch.utils.data import Dataset - -from taming.data.base import ImagePaths, NumpyPaths, ConcatDatasetWithIndex - - -class CustomBase(Dataset): - def __init__(self, *args, **kwargs): - super().__init__() - self.data = None - - def __len__(self): - return len(self.data) - - def __getitem__(self, i): - example = self.data[i] - return example - - - -class CustomTrain(CustomBase): - def __init__(self, size, training_images_list_file): - super().__init__() - with open(training_images_list_file, "r") as f: - paths = f.read().splitlines() - self.data = ImagePaths(paths=paths, size=size, random_crop=False) - - -class CustomTest(CustomBase): - def __init__(self, size, test_images_list_file): - super().__init__() - with open(test_images_list_file, "r") as f: - paths = f.read().splitlines() - self.data = ImagePaths(paths=paths, size=size, random_crop=False) - - diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fontTools/ufoLib/errors.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fontTools/ufoLib/errors.py deleted file mode 100644 index e05dd438b430708aac5163ebfde74ffb0501fbd1..0000000000000000000000000000000000000000 --- a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fontTools/ufoLib/errors.py +++ /dev/null @@ -1,22 +0,0 @@ -from __future__ import annotations - - -class UFOLibError(Exception): - pass - - -class UnsupportedUFOFormat(UFOLibError): - pass - - -class GlifLibError(UFOLibError): - def _add_note(self, note: str) -> None: - # Loose backport of PEP 678 until we only support Python 3.11+, used for - # adding additional context to errors. - # TODO: Replace with https://docs.python.org/3.11/library/exceptions.html#BaseException.add_note - (message, *rest) = self.args - self.args = ((message + "\n" + note), *rest) - - -class UnsupportedGLIFFormat(GlifLibError): - pass diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/jinja2/defaults.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/jinja2/defaults.py deleted file mode 100644 index 638cad3d2d8907330bde56e2b76c9b185c523b45..0000000000000000000000000000000000000000 --- a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/jinja2/defaults.py +++ /dev/null @@ -1,48 +0,0 @@ -import typing as t - -from .filters import FILTERS as DEFAULT_FILTERS # noqa: F401 -from .tests import TESTS as DEFAULT_TESTS # noqa: F401 -from .utils import Cycler -from .utils import generate_lorem_ipsum -from .utils import Joiner -from .utils import Namespace - -if t.TYPE_CHECKING: - import typing_extensions as te - -# defaults for the parser / lexer -BLOCK_START_STRING = "{%" -BLOCK_END_STRING = "%}" -VARIABLE_START_STRING = "{{" -VARIABLE_END_STRING = "}}" -COMMENT_START_STRING = "{#" -COMMENT_END_STRING = "#}" -LINE_STATEMENT_PREFIX: t.Optional[str] = None -LINE_COMMENT_PREFIX: t.Optional[str] = None -TRIM_BLOCKS = False -LSTRIP_BLOCKS = False -NEWLINE_SEQUENCE: "te.Literal['\\n', '\\r\\n', '\\r']" = "\n" -KEEP_TRAILING_NEWLINE = False - -# default filters, tests and namespace - -DEFAULT_NAMESPACE = { - "range": range, - "dict": dict, - "lipsum": generate_lorem_ipsum, - "cycler": Cycler, - "joiner": Joiner, - "namespace": Namespace, -} - -# default policies -DEFAULT_POLICIES: t.Dict[str, t.Any] = { - "compiler.ascii_str": True, - "urlize.rel": "noopener", - "urlize.target": None, - "urlize.extra_schemes": None, - "truncate.leeway": 5, - "json.dumps_function": None, - "json.dumps_kwargs": {"sort_keys": True}, - "ext.i18n.trimmed": False, -} diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/markdown_it/common/entities.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/markdown_it/common/entities.py deleted file mode 100644 index 6bb2d343c2338de4232378bf98d6c034fbe808c0..0000000000000000000000000000000000000000 --- a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/markdown_it/common/entities.py +++ /dev/null @@ -1,4 +0,0 @@ -"""HTML5 entities map: { name -> characters }.""" -import html.entities - -entities = {name.rstrip(";"): chars for name, chars in html.entities.html5.items()} diff --git a/spaces/dddmiku/vits-uma-genshin-honkai/text/cleaners.py b/spaces/dddmiku/vits-uma-genshin-honkai/text/cleaners.py deleted file mode 100644 index d26581deb399609163518054718ad80ecca5d934..0000000000000000000000000000000000000000 --- a/spaces/dddmiku/vits-uma-genshin-honkai/text/cleaners.py +++ /dev/null @@ -1,475 +0,0 @@ -""" from https://github.com/keithito/tacotron """ - -''' -Cleaners are transformations that run over the input text at both training and eval time. - -Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners" -hyperparameter. Some cleaners are English-specific. You'll typically want to use: - 1. "english_cleaners" for English text - 2. "transliteration_cleaners" for non-English text that can be transliterated to ASCII using - the Unidecode library (https://pypi.python.org/pypi/Unidecode) - 3. "basic_cleaners" if you do not want to transliterate (in this case, you should also update - the symbols in symbols.py to match your data). -''' - -import re -from unidecode import unidecode -import pyopenjtalk -from jamo import h2j, j2hcj -from pypinyin import lazy_pinyin, BOPOMOFO -import jieba, cn2an - - -# This is a list of Korean classifiers preceded by pure Korean numerals. -_korean_classifiers = '군데 권 개 그루 닢 대 두 마리 모 모금 뭇 발 발짝 방 번 벌 보루 살 수 술 시 쌈 움큼 정 짝 채 척 첩 축 켤레 톨 통' - -# Regular expression matching whitespace: -_whitespace_re = re.compile(r'\s+') - -# Regular expression matching Japanese without punctuation marks: -_japanese_characters = re.compile(r'[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]') - -# Regular expression matching non-Japanese characters or punctuation marks: -_japanese_marks = re.compile(r'[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]') - -# List of (regular expression, replacement) pairs for abbreviations: -_abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in [ - ('mrs', 'misess'), - ('mr', 'mister'), - ('dr', 'doctor'), - ('st', 'saint'), - ('co', 'company'), - ('jr', 'junior'), - ('maj', 'major'), - ('gen', 'general'), - ('drs', 'doctors'), - ('rev', 'reverend'), - ('lt', 'lieutenant'), - ('hon', 'honorable'), - ('sgt', 'sergeant'), - ('capt', 'captain'), - ('esq', 'esquire'), - ('ltd', 'limited'), - ('col', 'colonel'), - ('ft', 'fort'), -]] - -# List of (hangul, hangul divided) pairs: -_hangul_divided = [(re.compile('%s' % x[0]), x[1]) for x in [ - ('ㄳ', 'ㄱㅅ'), - ('ㄵ', 'ㄴㅈ'), - ('ㄶ', 'ㄴㅎ'), - ('ㄺ', 'ㄹㄱ'), - ('ㄻ', 'ㄹㅁ'), - ('ㄼ', 'ㄹㅂ'), - ('ㄽ', 'ㄹㅅ'), - ('ㄾ', 'ㄹㅌ'), - ('ㄿ', 'ㄹㅍ'), - ('ㅀ', 'ㄹㅎ'), - ('ㅄ', 'ㅂㅅ'), - ('ㅘ', 'ㅗㅏ'), - ('ㅙ', 'ㅗㅐ'), - ('ㅚ', 'ㅗㅣ'), - ('ㅝ', 'ㅜㅓ'), - ('ㅞ', 'ㅜㅔ'), - ('ㅟ', 'ㅜㅣ'), - ('ㅢ', 'ㅡㅣ'), - ('ㅑ', 'ㅣㅏ'), - ('ㅒ', 'ㅣㅐ'), - ('ㅕ', 'ㅣㅓ'), - ('ㅖ', 'ㅣㅔ'), - ('ㅛ', 'ㅣㅗ'), - ('ㅠ', 'ㅣㅜ') -]] - -# List of (Latin alphabet, hangul) pairs: -_latin_to_hangul = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [ - ('a', '에이'), - ('b', '비'), - ('c', '시'), - ('d', '디'), - ('e', '이'), - ('f', '에프'), - ('g', '지'), - ('h', '에이치'), - ('i', '아이'), - ('j', '제이'), - ('k', '케이'), - ('l', '엘'), - ('m', '엠'), - ('n', '엔'), - ('o', '오'), - ('p', '피'), - ('q', '큐'), - ('r', '아르'), - ('s', '에스'), - ('t', '티'), - ('u', '유'), - ('v', '브이'), - ('w', '더블유'), - ('x', '엑스'), - ('y', '와이'), - ('z', '제트') -]] - -# List of (Latin alphabet, bopomofo) pairs: -_latin_to_bopomofo = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [ - ('a', 'ㄟˉ'), - ('b', 'ㄅㄧˋ'), - ('c', 'ㄙㄧˉ'), - ('d', 'ㄉㄧˋ'), - ('e', 'ㄧˋ'), - ('f', 'ㄝˊㄈㄨˋ'), - ('g', 'ㄐㄧˋ'), - ('h', 'ㄝˇㄑㄩˋ'), - ('i', 'ㄞˋ'), - ('j', 'ㄐㄟˋ'), - ('k', 'ㄎㄟˋ'), - ('l', 'ㄝˊㄛˋ'), - ('m', 'ㄝˊㄇㄨˋ'), - ('n', 'ㄣˉ'), - ('o', 'ㄡˉ'), - ('p', 'ㄆㄧˉ'), - ('q', 'ㄎㄧㄡˉ'), - ('r', 'ㄚˋ'), - ('s', 'ㄝˊㄙˋ'), - ('t', 'ㄊㄧˋ'), - ('u', 'ㄧㄡˉ'), - ('v', 'ㄨㄧˉ'), - ('w', 'ㄉㄚˋㄅㄨˋㄌㄧㄡˋ'), - ('x', 'ㄝˉㄎㄨˋㄙˋ'), - ('y', 'ㄨㄞˋ'), - ('z', 'ㄗㄟˋ') -]] - - -# List of (bopomofo, romaji) pairs: -_bopomofo_to_romaji = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [ - ('ㄅㄛ', 'p⁼wo'), - ('ㄆㄛ', 'pʰwo'), - ('ㄇㄛ', 'mwo'), - ('ㄈㄛ', 'fwo'), - ('ㄅ', 'p⁼'), - ('ㄆ', 'pʰ'), - ('ㄇ', 'm'), - ('ㄈ', 'f'), - ('ㄉ', 't⁼'), - ('ㄊ', 'tʰ'), - ('ㄋ', 'n'), - ('ㄌ', 'l'), - ('ㄍ', 'k⁼'), - ('ㄎ', 'kʰ'), - ('ㄏ', 'h'), - ('ㄐ', 'ʧ⁼'), - ('ㄑ', 'ʧʰ'), - ('ㄒ', 'ʃ'), - ('ㄓ', 'ʦ`⁼'), - ('ㄔ', 'ʦ`ʰ'), - ('ㄕ', 's`'), - ('ㄖ', 'ɹ`'), - ('ㄗ', 'ʦ⁼'), - ('ㄘ', 'ʦʰ'), - ('ㄙ', 's'), - ('ㄚ', 'a'), - ('ㄛ', 'o'), - ('ㄜ', 'ə'), - ('ㄝ', 'e'), - ('ㄞ', 'ai'), - ('ㄟ', 'ei'), - ('ㄠ', 'au'), - ('ㄡ', 'ou'), - ('ㄧㄢ', 'yeNN'), - ('ㄢ', 'aNN'), - ('ㄧㄣ', 'iNN'), - ('ㄣ', 'əNN'), - ('ㄤ', 'aNg'), - ('ㄧㄥ', 'iNg'), - ('ㄨㄥ', 'uNg'), - ('ㄩㄥ', 'yuNg'), - ('ㄥ', 'əNg'), - ('ㄦ', 'əɻ'), - ('ㄧ', 'i'), - ('ㄨ', 'u'), - ('ㄩ', 'ɥ'), - ('ˉ', '→'), - ('ˊ', '↑'), - ('ˇ', '↓↑'), - ('ˋ', '↓'), - ('˙', ''), - ('，', ','), - ('。', '.'), - ('！', '!'), - ('？', '?'), - ('—', '-') -]] - - -def expand_abbreviations(text): - for regex, replacement in _abbreviations: - text = re.sub(regex, replacement, text) - return text - - -def lowercase(text): - return text.lower() - - -def collapse_whitespace(text): - return re.sub(_whitespace_re, ' ', text) - - -def convert_to_ascii(text): - return unidecode(text) - - -def japanese_to_romaji_with_accent(text): - '''Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html''' - sentences = re.split(_japanese_marks, text) - marks = re.findall(_japanese_marks, text) - text = '' - for i, sentence in enumerate(sentences): - if re.match(_japanese_characters, sentence): - if text!='': - text+=' ' - labels = pyopenjtalk.extract_fullcontext(sentence) - for n, label in enumerate(labels): - phoneme = re.search(r'\-([^\+]*)\+', label).group(1) - if phoneme not in ['sil','pau']: - text += phoneme.replace('ch','ʧ').replace('sh','ʃ').replace('cl','Q') - else: - continue - n_moras = int(re.search(r'/F:(\d+)_', label).group(1)) - a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1)) - a2 = int(re.search(r"\+(\d+)\+", label).group(1)) - a3 = int(re.search(r"\+(\d+)/", label).group(1)) - if re.search(r'\-([^\+]*)\+', labels[n + 1]).group(1) in ['sil','pau']: - a2_next=-1 - else: - a2_next = int(re.search(r"\+(\d+)\+", labels[n + 1]).group(1)) - # Accent phrase boundary - if a3 == 1 and a2_next == 1: - text += ' ' - # Falling - elif a1 == 0 and a2_next == a2 + 1 and a2 != n_moras: - text += '↓' - # Rising - elif a2 == 1 and a2_next == 2: - text += '↑' - if i torch.FloatTensor: - """ - Ensures interchangeability with schedulers that need to scale the denoising model input depending on the - current timestep. - - Args: - sample (`torch.FloatTensor`): input sample - timestep (`int`, optional): current timestep - - Returns: - `torch.FloatTensor`: scaled input sample - """ - return sample - - def set_timesteps( - self, num_inference_steps: int, sampling_eps: float = None, device: Union[str, torch.device] = None - ): - """ - Sets the continuous timesteps used for the diffusion chain. Supporting function to be run before inference. - - Args: - num_inference_steps (`int`): - the number of diffusion steps used when generating samples with a pre-trained model. - sampling_eps (`float`, optional): - final timestep value (overrides value given at Scheduler instantiation). - - """ - sampling_eps = sampling_eps if sampling_eps is not None else self.config.sampling_eps - - self.timesteps = torch.linspace(1, sampling_eps, num_inference_steps, device=device) - - def set_sigmas( - self, num_inference_steps: int, sigma_min: float = None, sigma_max: float = None, sampling_eps: float = None - ): - """ - Sets the noise scales used for the diffusion chain. Supporting function to be run before inference. - - The sigmas control the weight of the `drift` and `diffusion` components of sample update. - - Args: - num_inference_steps (`int`): - the number of diffusion steps used when generating samples with a pre-trained model. - sigma_min (`float`, optional): - initial noise scale value (overrides value given at Scheduler instantiation). - sigma_max (`float`, optional): - final noise scale value (overrides value given at Scheduler instantiation). - sampling_eps (`float`, optional): - final timestep value (overrides value given at Scheduler instantiation). - - """ - sigma_min = sigma_min if sigma_min is not None else self.config.sigma_min - sigma_max = sigma_max if sigma_max is not None else self.config.sigma_max - sampling_eps = sampling_eps if sampling_eps is not None else self.config.sampling_eps - if self.timesteps is None: - self.set_timesteps(num_inference_steps, sampling_eps) - - self.sigmas = sigma_min * (sigma_max / sigma_min) ** (self.timesteps / sampling_eps) - self.discrete_sigmas = torch.exp(torch.linspace(math.log(sigma_min), math.log(sigma_max), num_inference_steps)) - self.sigmas = torch.tensor([sigma_min * (sigma_max / sigma_min) ** t for t in self.timesteps]) - - def get_adjacent_sigma(self, timesteps, t): - return torch.where( - timesteps == 0, - torch.zeros_like(t.to(timesteps.device)), - self.discrete_sigmas[timesteps - 1].to(timesteps.device), - ) - - def step_pred( - self, - model_output: torch.FloatTensor, - timestep: int, - sample: torch.FloatTensor, - generator: Optional[torch.Generator] = None, - return_dict: bool = True, - ) -> Union[SdeVeOutput, Tuple]: - """ - Predict the sample at the previous timestep by reversing the SDE. Core function to propagate the diffusion - process from the learned model outputs (most often the predicted noise). - - Args: - model_output (`torch.FloatTensor`): direct output from learned diffusion model. - timestep (`int`): current discrete timestep in the diffusion chain. - sample (`torch.FloatTensor`): - current instance of sample being created by diffusion process. - generator: random number generator. - return_dict (`bool`): option for returning tuple rather than SchedulerOutput class - - Returns: - [`~schedulers.scheduling_sde_ve.SdeVeOutput`] or `tuple`: [`~schedulers.scheduling_sde_ve.SdeVeOutput`] if - `return_dict` is True, otherwise a `tuple`. When returning a tuple, the first element is the sample tensor. - - """ - if self.timesteps is None: - raise ValueError( - "`self.timesteps` is not set, you need to run 'set_timesteps' after creating the scheduler" - ) - - timestep = timestep * torch.ones( - sample.shape[0], device=sample.device - ) # torch.repeat_interleave(timestep, sample.shape[0]) - timesteps = (timestep * (len(self.timesteps) - 1)).long() - - # mps requires indices to be in the same device, so we use cpu as is the default with cuda - timesteps = timesteps.to(self.discrete_sigmas.device) - - sigma = self.discrete_sigmas[timesteps].to(sample.device) - adjacent_sigma = self.get_adjacent_sigma(timesteps, timestep).to(sample.device) - drift = torch.zeros_like(sample) - diffusion = (sigma**2 - adjacent_sigma**2) ** 0.5 - - # equation 6 in the paper: the model_output modeled by the network is grad_x log pt(x) - # also equation 47 shows the analog from SDE models to ancestral sampling methods - diffusion = diffusion.flatten() - while len(diffusion.shape) < len(sample.shape): - diffusion = diffusion.unsqueeze(-1) - drift = drift - diffusion**2 * model_output - - # equation 6: sample noise for the diffusion term of - noise = randn_tensor( - sample.shape, layout=sample.layout, generator=generator, device=sample.device, dtype=sample.dtype - ) - prev_sample_mean = sample - drift # subtract because `dt` is a small negative timestep - # TODO is the variable diffusion the correct scaling term for the noise? - prev_sample = prev_sample_mean + diffusion * noise # add impact of diffusion field g - - if not return_dict: - return (prev_sample, prev_sample_mean) - - return SdeVeOutput(prev_sample=prev_sample, prev_sample_mean=prev_sample_mean) - - def step_correct( - self, - model_output: torch.FloatTensor, - sample: torch.FloatTensor, - generator: Optional[torch.Generator] = None, - return_dict: bool = True, - ) -> Union[SchedulerOutput, Tuple]: - """ - Correct the predicted sample based on the output model_output of the network. This is often run repeatedly - after making the prediction for the previous timestep. - - Args: - model_output (`torch.FloatTensor`): direct output from learned diffusion model. - sample (`torch.FloatTensor`): - current instance of sample being created by diffusion process. - generator: random number generator. - return_dict (`bool`): option for returning tuple rather than SchedulerOutput class - - Returns: - [`~schedulers.scheduling_sde_ve.SdeVeOutput`] or `tuple`: [`~schedulers.scheduling_sde_ve.SdeVeOutput`] if - `return_dict` is True, otherwise a `tuple`. When returning a tuple, the first element is the sample tensor. - - """ - if self.timesteps is None: - raise ValueError( - "`self.timesteps` is not set, you need to run 'set_timesteps' after creating the scheduler" - ) - - # For small batch sizes, the paper "suggest replacing norm(z) with sqrt(d), where d is the dim. of z" - # sample noise for correction - noise = randn_tensor(sample.shape, layout=sample.layout, generator=generator).to(sample.device) - - # compute step size from the model_output, the noise, and the snr - grad_norm = torch.norm(model_output.reshape(model_output.shape[0], -1), dim=-1).mean() - noise_norm = torch.norm(noise.reshape(noise.shape[0], -1), dim=-1).mean() - step_size = (self.config.snr * noise_norm / grad_norm) ** 2 * 2 - step_size = step_size * torch.ones(sample.shape[0]).to(sample.device) - # self.repeat_scalar(step_size, sample.shape[0]) - - # compute corrected sample: model_output term and noise term - step_size = step_size.flatten() - while len(step_size.shape) < len(sample.shape): - step_size = step_size.unsqueeze(-1) - prev_sample_mean = sample + step_size * model_output - prev_sample = prev_sample_mean + ((step_size * 2) ** 0.5) * noise - - if not return_dict: - return (prev_sample,) - - return SchedulerOutput(prev_sample=prev_sample) - - def add_noise( - self, - original_samples: torch.FloatTensor, - noise: torch.FloatTensor, - timesteps: torch.FloatTensor, - ) -> torch.FloatTensor: - # Make sure sigmas and timesteps have the same device and dtype as original_samples - timesteps = timesteps.to(original_samples.device) - sigmas = self.discrete_sigmas.to(original_samples.device)[timesteps] - noise = torch.randn_like(original_samples) * sigmas[:, None, None, None] - noisy_samples = noise + original_samples - return noisy_samples - - def __len__(self): - return self.config.num_train_timesteps diff --git a/spaces/declare-lab/tango/diffusers/tests/pipelines/dance_diffusion/__init__.py b/spaces/declare-lab/tango/diffusers/tests/pipelines/dance_diffusion/__init__.py deleted file mode 100644 index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000 diff --git a/spaces/deepwisdom/MetaGPT/metagpt/memory/longterm_memory.py b/spaces/deepwisdom/MetaGPT/metagpt/memory/longterm_memory.py deleted file mode 100644 index 041d335acbac81ef5cd98aa158aa70600d62dec7..0000000000000000000000000000000000000000 --- a/spaces/deepwisdom/MetaGPT/metagpt/memory/longterm_memory.py +++ /dev/null @@ -1,73 +0,0 @@ -#!/usr/bin/env python -# -*- coding: utf-8 -*- -""" -@Desc : the implement of Long-term memory -@Modified By: mashenquan, 2023/8/20. Remove global configuration `CONFIG`, enable configuration support for business isolation. -""" - -from metagpt.logs import logger -from metagpt.memory import Memory -from metagpt.memory.memory_storage import MemoryStorage -from metagpt.schema import Message - - -class LongTermMemory(Memory): - """ - The Long-term memory for Roles - - recover memory when it staruped - - update memory when it changed - """ - - def __init__(self): - self.memory_storage: MemoryStorage = MemoryStorage() - super(LongTermMemory, self).__init__() - self.rc = None # RoleContext - self.msg_from_recover = False - - def recover_memory(self, role_id: str, rc: "RoleContext"): - messages = self.memory_storage.recover_memory(role_id) - self.rc = rc - if not self.memory_storage.is_initialized: - logger.warning(f"It may the first time to run Agent {role_id}, the long-term memory is empty") - else: - logger.warning( - f"Agent {role_id} has existed memory storage with {len(messages)} messages " f"and has recovered them." - ) - self.msg_from_recover = True - self.add_batch(messages) - self.msg_from_recover = False - - def add(self, message: Message, **kwargs): - super(LongTermMemory, self).add(message) - for action in self.rc.watch: - if message.cause_by == action and not self.msg_from_recover: - # currently, only add role's watching messages to its memory_storage - # and ignore adding messages from recover repeatedly - self.memory_storage.add(message, **kwargs) - - def remember(self, observed: list[Message], k=0) -> list[Message]: - """ - remember the most similar k memories from observed Messages, return all when k=0 - 1. remember the short-term memory(stm) news - 2. integrate the stm news with ltm(long-term memory) news - """ - stm_news = super(LongTermMemory, self).remember(observed, k=k) # shot-term memory news - if not self.memory_storage.is_initialized: - # memory_storage hasn't initialized, use default `remember` to get stm_news - return stm_news - - ltm_news: list[Message] = [] - for mem in stm_news: - # integrate stm & ltm - mem_searched = self.memory_storage.search(mem) - if len(mem_searched) > 0: - ltm_news.append(mem) - return ltm_news[-k:] - - def delete(self, message: Message): - super(LongTermMemory, self).delete(message) - # TODO delete message in memory_storage - - def clear(self): - super(LongTermMemory, self).clear() - self.memory_storage.clean() diff --git a/spaces/deven367/yt-video-annotator-hf/README.md b/spaces/deven367/yt-video-annotator-hf/README.md deleted file mode 100644 index 542a02da8454c9a531c97edd43c0aaa1e61db7dd..0000000000000000000000000000000000000000 --- a/spaces/deven367/yt-video-annotator-hf/README.md +++ /dev/null @@ -1,28 +0,0 @@ ---- -title: Yt Video Annotator -emoji: 🐢 -colorFrom: green -colorTo: blue -sdk: streamlit -sdk_version: 1.25.0 -app_file: app.py -pinned: false ---- - -## Try the app on hf-spaces - -You can find the deployed app → [**here**](https://huggingface.co/spaces/deven367/yt-video-annotator/) - -> **Note** -> The app inference is slow as the inference is running on a CPU, if you have GPU on your local system, the app will work a lot faster. - -## Installation - -1. 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