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EmoHugAI/pegasus-samsum | EmoHugAI | 2024-07-02T00:42:22Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:42:22Z | Entry not found |
habulaj/11777192364 | habulaj | 2024-07-02T00:43:08Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:43:04Z | Entry not found |
valerielucro/mistral_gsm8k_sft_v1_epoch5 | valerielucro | 2024-07-02T00:44:14Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T00:43:30Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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[More Information Needed]
## Bias, Risks, and Limitations
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### Recommendations
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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[More Information Needed]
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#### Summary
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[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]
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habulaj/251274222352 | habulaj | 2024-07-02T00:45:43Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:45:34Z | Entry not found |
marianbasti/XTTS-v2-argentinian-spanish | marianbasti | 2024-07-02T14:49:28Z | 0 | 0 | coqui | [
"coqui",
"text-to-speech",
"es",
"dataset:ylacombe/google-argentinian-spanish",
"license:other",
"region:us"
] | text-to-speech | 2024-07-02T00:46:55Z | ---
license: other
license_name: coqui-public-model-license
license_link: https://coqui.ai/cpml
library_name: coqui
pipeline_tag: text-to-speech
datasets:
- ylacombe/google-argentinian-spanish
language:
- es
---
# ⓍTTS 🇦🇷
ⓍTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 6-second audio clip. There is no need for an excessive amount of training data that spans countless hours.
This model was trained by [CITECCA](https://mapatecnologico.rionegro.gov.ar/detail/citecca-centro-interdisciplinario-de-telecomunicaciones-electronica-computacion-y-ciencia-aplicada-unrn) in the [Universidad Nacional de Rio Negro](https://www.unrn.edu.ar/home)
### Language
This model's Spanish language has been finetuned using [ylacombe's google argentinian spanish dataset](https://huggingface.co/datasets/ylacombe/google-argentinian-spanish) to archieve an argentinian accent.
### Training Parameters
```
batch_size=8,
grad_accum_steps=96,
batch_group_size=48,
eval_batch_size=8,
num_loader_workers=8,
eval_split_max_size=256,
optimizer="AdamW",
optimizer_wd_only_on_weights=True,
optimizer_params={"betas": [0.9, 0.96], "eps": 1e-8, "weight_decay": 1e-2},
lr=5e-06,
lr_scheduler="MultiStepLR",
lr_scheduler_params={"milestones": [50000 * 18, 150000 * 18, 300000 * 18], "gamma": 0.5, "last_epoch": -1},
```
### License
This model is licensed under [Coqui Public Model License](https://coqui.ai/cpml). There's a lot that goes into a license for generative models, and you can read more of [the origin story of CPML here](https://coqui.ai/blog/tts/cpml).
Using 🐸TTS Command line:
```console
tts --model_name /path/to/xtts/ \
--text "Che boludo, vamos a tomar unos mates." \
--speaker_wav /path/to/target/speaker.wav \
--language_idx es \
--use_cuda true
```
Using the model directly:
```python
from TTS.tts.configs.xtts_config import XttsConfig
from TTS.tts.models.xtts import Xtts
config = XttsConfig()
config.load_json("/path/to/xtts/config.json")
model = Xtts.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="/path/to/xtts/", eval=True)
model.cuda()
outputs = model.synthesize(
"Che boludo, vamos a tomar unos mates.",
config,
speaker_wav="/data/TTS-public/_refclips/3.wav",
gpt_cond_len=3,
language="es",
)
``` |
Piotrasz/Llama-2-7b-hf-R_ROME-50-en | Piotrasz | 2024-07-02T00:52:22Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-02T00:49:15Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
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[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
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#### Speeds, Sizes, Times [optional]
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#### Testing Data
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#### Metrics
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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habulaj/9953886210 | habulaj | 2024-07-02T00:50:51Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:50:45Z | Entry not found |
nodirjon/whisper-small-uz | nodirjon | 2024-07-02T04:55:46Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"uz",
"dataset:mozilla-foundation/common_voice_11_0",
"base_model:openai/whisper-small",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-02T00:51:01Z | ---
language:
- uz
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: Whisper Small UZ - Nodirjon Muxammadaliyev
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small UZ - Nodirjon Muxammadaliyev
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.42.3
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
valerielucro/mistral_gsm8k_sft_v2_epoch4 | valerielucro | 2024-07-02T00:51:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T00:51:17Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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TomEijkelenkamp/renaissance-llava-focus | TomEijkelenkamp | 2024-07-02T00:52:11Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:52:11Z | Entry not found |
sean-lamont/deepseek-base-novel | sean-lamont | 2024-07-02T01:08:54Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:deepseek-ai/deepseek-math-7b-base",
"region:us"
] | null | 2024-07-02T00:54:59Z | ---
library_name: peft
base_model: deepseek-ai/deepseek-math-7b-base
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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[More Information Needed]
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[More Information Needed]
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
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#### Preprocessing [optional]
[More Information Needed]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
## More Information [optional]
[More Information Needed]
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[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.11.1 |
Allan01F/PontoZen | Allan01F | 2024-07-02T00:58:00Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:58:00Z | Entry not found |
junyoung01/tsart3d | junyoung01 | 2024-07-02T01:03:49Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:58:34Z | Entry not found |
suosuo321/293 | suosuo321 | 2024-07-02T01:09:42Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T00:58:44Z | Invalid username or password. |
joycewu/whisper-small-hi | joycewu | 2024-07-02T01:00:30Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:00:30Z | Entry not found |
lsef/finetuning-1 | lsef | 2024-07-02T01:06:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T01:02:56Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Hardware Type:** [More Information Needed]
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blockblockblock/Tess-v2.5-Phi-3-medium-128k-14B-bpw6-exl2 | blockblockblock | 2024-07-02T01:04:53Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:04:53Z | Entry not found |
Ewopally/my_awesome_opus_books_model | Ewopally | 2024-07-02T01:10:12Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:10:12Z | Entry not found |
minyichen/Llama-3-Taiwan-70B-Instruct-GPTQ | minyichen | 2024-07-02T13:48:44Z | 0 | 2 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-3",
"conversational",
"zh",
"en",
"base_model:yentinglin/Llama-3-Taiwan-70B-Instruct",
"license:llama3",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"gptq",
"region:us"
] | text-generation | 2024-07-02T01:13:36Z | ---
base_model: yentinglin/Llama-3-Taiwan-70B-Instruct
language:
- zh
- en
license: llama3
model_creator: yentinglin
model_name: Llama-3-Taiwan-70B-Instruct
model_type: llama
pipeline_tag: text-generation
quantized_by: minyichen
tags:
- llama-3
---
# Llama-3-Taiwan-70B-Instruct - GPTQ
- Model creator: [Yen-Ting Lin](https://huggingface.co/yentinglin)
- Original model: [Llama-3-Taiwan-70B-Instruct](https://huggingface.co/yentinglin/Llama-3-Taiwan-70B-Instruct)
<!-- description start -->
## Description
This repo contains GPTQ model files for [Llama-3-Taiwan-70B-Instruct](https://huggingface.co/yentinglin/Llama-3-Taiwan-70B-Instruct).
<!-- description end -->
<!-- repositories-available start -->
* [GPTQ models for GPU inference](minyichen/Llama-3-Taiwan-70B-Instruct-GPTQ)
* [Yen-Ting Lin's original unquantized model](https://huggingface.co/yentinglin/Llama-3-Taiwan-70B-Instruct)
<!-- repositories-available end -->
## Quantization parameter
- Bits : 4
- Group Size : 128
- Act Order : Yes
- Damp % : 0.01
- Seq Len : 2048
- Size : 37.07 GB
|
mago18/ava-50-chose2 | mago18 | 2024-07-02T01:15:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T01:14:32Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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mathabes/teste-llama3 | mathabes | 2024-07-02T01:14:52Z | 0 | 0 | null | [
"license:llama3",
"region:us"
] | null | 2024-07-02T01:14:52Z | ---
license: llama3
---
|
PhucDanh/ViT5-fine-tuning-on-UIT-Course-information | PhucDanh | 2024-07-02T01:28:18Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"question-answering",
"license:mit",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | question-answering | 2024-07-02T01:16:48Z | ---
license: mit
---
|
Charles95/autotrain-qwen2-7b-instruction-sft-int4 | Charles95 | 2024-07-02T01:18:10Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-07-02T01:18:10Z | Temporary Redirect. Redirecting to /Charles95/autotrain-qwen2-7b-instruction-sft-int8/resolve/main/README.md |
qfox/dafuse | qfox | 2024-07-02T01:19:06Z | 0 | 1 | null | [
"region:us"
] | null | 2024-07-02T01:19:06Z | Entry not found |
liminerity/Bitnet-Mistral.0.2-33m-v0.2-grokfast | liminerity | 2024-07-02T01:19:45Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-07-02T01:19:45Z | ---
license: apache-2.0
---
|
CatBarks/t5-lora-squad_model70 | CatBarks | 2024-07-02T01:19:52Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T01:19:48Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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[More Information Needed]
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[More Information Needed]
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CatBarks/t5-lora-squad_tokenizer70 | CatBarks | 2024-07-02T01:19:53Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T01:19:52Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
## Training Details
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<!-- Relevant interpretability work for the model goes here -->
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jay6944/EEVE-Korean-Instruct-10.8B-geoheim20-8bit | jay6944 | 2024-07-02T02:56:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"conversational",
"en",
"base_model:yanolja/EEVE-Korean-Instruct-10.8B-v1.0",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-02T01:21:22Z | ---
base_model: yanolja/EEVE-Korean-Instruct-10.8B-v1.0
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** jay6944
- **License:** apache-2.0
- **Finetuned from model :** yanolja/EEVE-Korean-Instruct-10.8B-v1.0
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
senhorsapo/batman | senhorsapo | 2024-07-02T01:22:36Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2024-07-02T01:22:18Z | ---
license: openrail
---
|
teddybearz/zephyr-7b-sft-full | teddybearz | 2024-07-02T01:24:34Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:24:34Z | Entry not found |
vgangal101/distilbert-base-uncased-finetuned-imdb | vgangal101 | 2024-07-02T01:24:37Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:24:37Z | Entry not found |
seonggyun/bottle_mask | seonggyun | 2024-07-02T07:12:19Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"lora",
"base_model:CompVis/stable-diffusion-v1-4",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2024-07-02T01:24:51Z |
---
license: creativeml-openrail-m
base_model: CompVis/stable-diffusion-v1-4
instance_prompt: a photo of sks mask
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
inference: true
---
# LoRA DreamBooth - seonggyun/bottle_mask
These are LoRA adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks mask using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
|
habulaj/6905451062 | habulaj | 2024-07-02T01:26:30Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:26:26Z | Entry not found |
habulaj/5697843432 | habulaj | 2024-07-02T01:27:09Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:27:03Z | Entry not found |
yehiawp4/vivit-b-16x2-mixed-dataset | yehiawp4 | 2024-07-02T21:52:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vivit",
"video-classification",
"generated_from_trainer",
"base_model:google/vivit-b-16x2-kinetics400",
"license:mit",
"endpoints_compatible",
"region:us"
] | video-classification | 2024-07-02T01:27:29Z | ---
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-mixed-dataset
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vivit-b-16x2-mixed-dataset
This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1118
- Accuracy: 0.9740
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 7044
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2111 | 0.17 | 1174 | 0.8879 | 0.7863 |
| 0.0911 | 1.17 | 2348 | 0.5390 | 0.8831 |
| 0.0021 | 2.17 | 3522 | 0.2326 | 0.9355 |
| 0.0028 | 3.17 | 4696 | 0.3125 | 0.9395 |
| 0.0008 | 4.17 | 5870 | 0.3077 | 0.9476 |
| 0.125 | 5.17 | 7044 | 0.1982 | 0.9617 |
### Framework versions
- Transformers 4.39.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.15.2
|
guillermoasto/guilermino | guillermoasto | 2024-07-02T01:29:42Z | 0 | 0 | null | [
"es",
"dataset:Sao10K/Claude-3-Opus-Instruct-15K",
"license:mit",
"region:us"
] | null | 2024-07-02T01:28:40Z | ---
license: mit
datasets:
- Sao10K/Claude-3-Opus-Instruct-15K
language:
- es
metrics:
- cer
--- |
didikmarjadi/marjadi | didikmarjadi | 2024-07-02T01:28:57Z | 0 | 0 | null | [
"license:other",
"region:us"
] | null | 2024-07-02T01:28:57Z | ---
license: other
license_name: didik
license_link: LICENSE
---
|
habulaj/3184030062 | habulaj | 2024-07-02T01:29:07Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:28:59Z | Entry not found |
fokyoum9/Solar_KO_ORCA_Test10 | fokyoum9 | 2024-07-02T01:30:12Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:30:12Z | Entry not found |
KolaGang/Ironic | KolaGang | 2024-07-02T04:22:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"axolotl",
"generated_from_trainer",
"conversational",
"base_model:google/gemma-2-27b",
"license:gemma",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-02T01:32:17Z | ---
license: gemma
base_model: google/gemma-2-27b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: Ironic
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.1`
```yaml
base_model: google/gemma-2-27b
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
hub_model_id: KolaGang/Ironic
hub_strategy: end
# huggingface repo
chat_template: gemma
datasets:
- path: KolaGang/Reflection
type: reflection
- path: KolaGang/RAG_EAI
type: context_qa.load_v2
- path: lighteval/legal_summarization
name: BillSum
type: summarizetldr
- path: KolaGang/QA
type: alpaca_chat.load_qa
- path: KolaGang/chatlaw
type: sharegpt
- path: KolaGang/draft
type: alpaca
- path: KolaGang/alpca_w_system
type: alpaca
- path: teknium/dataforge-economics
type: sharegpt
val_set_size: 0.0
output_dir: ./outputs/out
sequence_len: 2048
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
wandb_project: QwenQwen
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model: smalqwen
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0005
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 100
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
special_tokens:
```
</details><br>
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dangfutures/QwenQwen/runs/fidneg52)
# Ironic
This model is a fine-tuned version of [google/gemma-2-27b](https://huggingface.co/google/gemma-2-27b) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
### Training results
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|
Cret/Char.Hsr | Cret | 2024-07-02T01:37:08Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:32:49Z | Entry not found |
blockblockblock/Tess-v2.5-Phi-3-medium-128k-14B-bpw5-exl2 | blockblockblock | 2024-07-02T01:42:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"generated_from_trainer",
"conversational",
"custom_code",
"base_model:microsoft/Phi-3-medium-128k-instruct",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"5-bit",
"exl2",
"region:us"
] | text-generation | 2024-07-02T01:32:54Z | ---
license: mit
base_model: microsoft/Phi-3-medium-128k-instruct
tags:
- generated_from_trainer
model-index:
- name: migtissera/Tess-v2.5-Phi-3-medium-128k-14B
results: []
---
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# Prompt Format
ChatML
|
novanm/cccc | novanm | 2024-07-02T01:34:32Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:34:32Z | Entry not found |
habulaj/1526715044 | habulaj | 2024-07-02T01:35:42Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:35:23Z | Entry not found |
SeungWooNAM/new_tokenizer_v1 | SeungWooNAM | 2024-07-02T01:35:39Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T01:35:38Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
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[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] |
habulaj/1318813313 | habulaj | 2024-07-02T01:36:53Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:36:51Z | Entry not found |
habulaj/310201277108 | habulaj | 2024-07-02T01:38:48Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:38:39Z | Entry not found |
0xfaskety/Qwen-Qwen2-1.5B-1719884471 | 0xfaskety | 2024-07-02T01:41:18Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-1.5B",
"region:us"
] | null | 2024-07-02T01:41:11Z | ---
library_name: peft
base_model: Qwen/Qwen2-1.5B
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.11.1 |
iasjkk/MV_Final_6000_Iter | iasjkk | 2024-07-02T01:43:31Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:43:31Z | Entry not found |
ninonakano2/Glaucoma | ninonakano2 | 2024-07-02T01:57:18Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-02T01:44:17Z | ---
license: mit
---
|
Enzo87/87 | Enzo87 | 2024-07-02T01:47:02Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:47:02Z | Entry not found |
reiffd/bert-base-phia-name-1k | reiffd | 2024-07-02T01:49:20Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:49:20Z | Entry not found |
gokulsrinivasagan/gpt_48 | gokulsrinivasagan | 2024-07-02T01:49:54Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:49:54Z | ---
license: mit
base_model: gokulsrinivasagan/gpt_36
tags:
- generated_from_trainer
datasets:
- gokuls/wiki_book_corpus_complete_raw_dataset
metrics:
- accuracy
model-index:
- name: gpt_48
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: gokuls/wiki_book_corpus_complete_raw_dataset
type: gokuls/wiki_book_corpus_complete_raw_dataset
metrics:
- name: Accuracy
type: accuracy
value: 0.36499145150873114
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/gokulsrinivasagan/huggingface/runs/gokrhr03)
# gpt_48
This model is a fine-tuned version of [gokulsrinivasagan/gpt_36](https://huggingface.co/gokulsrinivasagan/gpt_36) on the gokuls/wiki_book_corpus_complete_raw_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2538
- Accuracy: 0.3650
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
### Training results
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|
rinogrego/GritLM-BioMedLM-8-bit | rinogrego | 2024-07-02T01:52:36Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:52:36Z | Entry not found |
Ahmedalla/whisper-largev3-ms | Ahmedalla | 2024-07-02T01:53:26Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:53:26Z | Entry not found |
kamelliao/hotpot-ce-0701 | kamelliao | 2024-07-02T01:55:49Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/flan-t5-xl",
"region:us"
] | null | 2024-07-02T01:55:24Z | ---
base_model: google/flan-t5-xl
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
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[More Information Needed]
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[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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### Framework versions
- PEFT 0.11.1 |
Prismchen/llama-3-8b-chat-doctor-3 | Prismchen | 2024-07-02T01:59:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T01:56:56Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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[More Information Needed]
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[More Information Needed]
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Ocastano/mini-gpt-1 | Ocastano | 2024-07-02T03:33:28Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:57:13Z | Entry not found |
0xfaskety/Qwen-Qwen2-1.5B-1719885448 | 0xfaskety | 2024-07-02T01:57:37Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-1.5B",
"region:us"
] | null | 2024-07-02T01:57:28Z | ---
library_name: peft
base_model: Qwen/Qwen2-1.5B
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
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[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
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[More Information Needed]
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[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
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## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
## More Information [optional]
[More Information Needed]
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[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.11.1 |
habulaj/10877383718 | habulaj | 2024-07-02T01:58:39Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T01:58:35Z | Entry not found |
habulaj/179207154060 | habulaj | 2024-07-02T02:01:05Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:01:03Z | Entry not found |
habulaj/4488479679 | habulaj | 2024-07-02T02:03:23Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:03:19Z | Entry not found |
blockblockblock/Tess-v2.5-Phi-3-medium-128k-14B-bpw5.5-exl2 | blockblockblock | 2024-07-02T02:14:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"generated_from_trainer",
"conversational",
"custom_code",
"base_model:microsoft/Phi-3-medium-128k-instruct",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"exl2",
"region:us"
] | text-generation | 2024-07-02T02:04:19Z | ---
license: mit
base_model: microsoft/Phi-3-medium-128k-instruct
tags:
- generated_from_trainer
model-index:
- name: migtissera/Tess-v2.5-Phi-3-medium-128k-14B
results: []
---
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# Prompt Format
ChatML
|
yongjinchoi/sdxl-webtoon-model2 | yongjinchoi | 2024-07-02T10:02:36Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"text-to-image",
"diffusers-training",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:creativeml-openrail-m",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | 2024-07-02T02:04:24Z | ---
license: creativeml-openrail-m
library_name: diffusers
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers-training
- diffusers
base_model: stabilityai/stable-diffusion-xl-base-1.0
inference: true
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# Text-to-image finetuning - yongjinchoi/sdxl-webtoon-model2
This pipeline was finetuned from **stabilityai/stable-diffusion-xl-base-1.0** on the **None** dataset. Below are some example images generated with the finetuned pipeline using the following prompt: a man with sad expression, wearing red shirt, waiting for taxi, side view.:
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
## Intended uses & limitations
#### How to use
```python
# TODO: add an example code snippet for running this diffusion pipeline
```
#### Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
## Training details
[TODO: describe the data used to train the model] |
coatedincrimson/BTSNamjoon | coatedincrimson | 2024-07-02T02:08:18Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2024-07-02T02:06:04Z | ---
license: openrail
---
|
taehyunzzz/switch-base-8-samsum-top-2 | taehyunzzz | 2024-07-02T06:12:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"switch_transformers",
"text2text-generation",
"generated_from_trainer",
"dataset:samsum",
"base_model:google/switch-base-8",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text2text-generation | 2024-07-02T02:09:59Z | ---
license: apache-2.0
base_model: google/switch-base-8
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: switch-base-8-samsum-top-2
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: validation
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 46.9043
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# switch-base-8-samsum-top-2
This model is a fine-tuned version of [google/switch-base-8](https://huggingface.co/google/switch-base-8) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4628
- Rouge1: 46.9043
- Rouge2: 23.9322
- Rougel: 39.7156
- Rougelsum: 43.4676
- Gen Len: 16.901
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.9271 | 0.4343 | 100 | 2.5447 | 31.6934 | 12.2905 | 27.3193 | 29.2988 | 13.9181 |
| 2.1187 | 0.8686 | 200 | 1.6903 | 42.983 | 20.5156 | 36.2755 | 40.0063 | 15.9144 |
| 1.9821 | 1.3029 | 300 | 1.6019 | 44.9046 | 22.2699 | 37.7936 | 41.6403 | 16.3778 |
| 1.8929 | 1.7372 | 400 | 1.5481 | 45.6301 | 22.3458 | 38.336 | 42.1537 | 16.8729 |
| 1.7636 | 2.1716 | 500 | 1.5220 | 46.0005 | 22.9639 | 38.7817 | 42.6503 | 16.6394 |
| 1.7915 | 2.6059 | 600 | 1.5013 | 46.3959 | 23.2583 | 39.1003 | 43.0423 | 16.9584 |
| 1.6986 | 3.0402 | 700 | 1.4833 | 46.5621 | 23.3536 | 39.2009 | 43.0652 | 16.8949 |
| 1.7058 | 3.4745 | 800 | 1.4744 | 46.4686 | 23.3191 | 39.164 | 43.0955 | 16.7494 |
| 1.6554 | 3.9088 | 900 | 1.4719 | 46.9026 | 23.6865 | 39.4972 | 43.4464 | 16.9792 |
| 1.6459 | 4.3431 | 1000 | 1.4637 | 46.7478 | 23.5211 | 39.4003 | 43.3027 | 16.9768 |
| 1.6889 | 4.7774 | 1100 | 1.4628 | 46.9043 | 23.9322 | 39.7156 | 43.4676 | 16.901 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
|
jkmeng/modelt | jkmeng | 2024-07-02T02:10:00Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-07-02T02:10:00Z | ---
license: apache-2.0
---
|
Alexfierce/Alexfierce | Alexfierce | 2024-07-02T02:10:22Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:10:22Z | Entry not found |
jiequan/clip-roberta-finetuned | jiequan | 2024-07-02T14:24:01Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vision-text-dual-encoder",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2024-07-02T02:10:25Z | Entry not found |
habulaj/548750525562 | habulaj | 2024-07-02T02:10:48Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:10:27Z | Entry not found |
davidyu2023/Qwen-Qwen1.5-0.5B-1719886257 | davidyu2023 | 2024-07-02T02:11:05Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | 2024-07-02T02:10:58Z | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
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<!-- Provide the basic links for the model. -->
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- **Paper [optional]:** [More Information Needed]
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.11.1 |
1231czx/7b_dpo_iter3_4e7_step200_onpolicy_only | 1231czx | 2024-07-02T02:15:42Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-02T02:12:18Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Ewopally/my_awesome_billsum_model | Ewopally | 2024-07-02T02:13:56Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:13:56Z | Entry not found |
little-public-up/KADIS700 | little-public-up | 2024-07-02T16:53:32Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:14:28Z | Entry not found |
Desubicator/mergeD5 | Desubicator | 2024-07-02T02:22:42Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"license:cc",
"region:us"
] | null | 2024-07-02T02:15:22Z | ---
license: cc
---
|
valerielucro/mistral_gsm8k_sft_v1_epoch6 | valerielucro | 2024-07-02T02:16:28Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T02:15:47Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
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jclian91/Qwen2-72B-Instruct-math | jclian91 | 2024-07-02T03:24:13Z | 0 | 0 | null | [
"license:bsd",
"region:us"
] | null | 2024-07-02T02:16:21Z | ---
license: bsd
---
Welcome to Qwen2-72B-Instruct-math model, which is used for solving Math Problem.
<div align="center">
<h1>Welcome to LLM Math Solver</h1>
<h4 align="center">
<a href="https://percent4.github.io/llm_math_solver/"><img src="https://img.shields.io/badge/📄-docs-000000?style=for-the-badge&colorA=09c&colorB=555" height='35px' alt="Docs"></a>
</h4>
<p>LLM Math Solver: using LLM to solve MATH problems.
</p>
<h1></h1>
</div>
## 评估结果
不同模型经过微调的数学能力测评表如下：
| 基座模型 | GSM8K | MATH | 样本数 |
|---------------------|--------|--------|------|
| QWen1.5-32B | 79.68% | 43.58% | 2402 |
| Yi-1.5-34B | 83.47% | 52.76% | 3480 |
| Yi-1.5-34B-Chat | 85.67% | 57.22% | 3479 |
| QWen-2-72B-Instruct | **93.03%** | **68.54%** | 3469 |
其它模型：
|模型|GSM8K | MATH|
|---|---|---|
|GPT-4o-0513|95.8%|76.6%|
|Claude-3.5-Sonnet|96.4%|71.1%|
|GEMINI-1.5-PRO(May 2024)|/|67.7%|
|DeepSeek-Coder-V2-Instruct(236B)|94.9%|75.7%|
## 使用方法
## 参考文献
关于该模型使用的训练数据、训练方法和相关文章，可以参考Github上项目: [llm_math_solver](https://github.com/percent4/llm_math_solver).
文章如下：
1. [NLP（九十七）大模型数学解题能力的初步探索](https://mp.weixin.qq.com/s?__biz=MzU2NTYyMDk5MQ==&mid=2247486824&idx=1&sn=fd6b36cf78aead227359606a7270516d&chksm=fcb9b4f8cbce3dee332335092f576c703ccdc55598cf45cb7f483f822ba5c72590019384d12a&token=321761101&lang=zh_CN#rd)
2. [NLP（九十九）大模型的数学能力微调及测评](https://mp.weixin.qq.com/s?__biz=MzU2NTYyMDk5MQ==&mid=2247486889&idx=1&sn=27c1a40d3af462f43a80a1ed401843f6&chksm=fcb9b439cbce3d2fd73e753618e0b32027314648eb13dc8b48bb9e713ad5313777c1ef27ce46&token=390124673&lang=zh_CN#rd)
3. [NLP（一百）大模型数学能力测评](https://mp.weixin.qq.com/s?__biz=MzU2NTYyMDk5MQ==&mid=2247486909&idx=1&sn=31b01bd4155b2c9ca15e2a7ae9f4de15&chksm=fcb9b42dcbce3d3bb473cf138f0f0f9a71addeff934900d155b6b90fb2a5857c1926b8aa0e9d&token=584142844&lang=zh_CN#rd)
4. [Open WebUI的Pipelines学习之使用大模型解数学题](https://mp.weixin.qq.com/s?__biz=MzU2NTYyMDk5MQ==&mid=2247487013&idx=1&sn=6a6786ba8c8c7cfdbc02ef558adefe71&chksm=fcb9b7b5cbce3ea37f8fb61e743d0ea0a7d4f5d6b8e8b2c7a80171a5c8c217524d8f307c0146&token=120899150&lang=zh_CN#rd) |
munasco/whisper-small-hi | munasco | 2024-07-03T00:50:03Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-02T02:16:53Z | Entry not found |
OniSJ/course_faq_bot | OniSJ | 2024-07-02T02:17:20Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-02T02:17:20Z | ---
license: mit
---
|
davidyu2023/Qwen-Qwen1.5-1.8B-1719886656 | davidyu2023 | 2024-07-02T02:17:41Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | 2024-07-02T02:17:36Z | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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[More Information Needed]
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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habulaj/186366160620 | habulaj | 2024-07-02T02:19:19Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:19:17Z | Entry not found |
habulaj/2843528076 | habulaj | 2024-07-02T02:20:54Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:20:52Z | Entry not found |
davidyu2023/google-gemma-2b-1719886961 | davidyu2023 | 2024-07-02T02:22:54Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"region:us"
] | null | 2024-07-02T02:22:41Z | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
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[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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[More Information Needed]
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[More Information Needed]
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### Framework versions
- PEFT 0.11.1 |
taehyunzzz/switch-base-8-samsum-top-1 | taehyunzzz | 2024-07-02T09:06:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"switch_transformers",
"text2text-generation",
"generated_from_trainer",
"dataset:samsum",
"base_model:google/switch-base-8",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text2text-generation | 2024-07-02T02:23:03Z | ---
license: apache-2.0
base_model: google/switch-base-8
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: switch-base-8-samsum-top-1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: validation
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 47.5943
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# switch-base-8-samsum-top-1
This model is a fine-tuned version of [google/switch-base-8](https://huggingface.co/google/switch-base-8) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4424
- Rouge1: 47.5943
- Rouge2: 24.4996
- Rougel: 40.2349
- Rougelsum: 43.9923
- Gen Len: 17.0342
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.4048 | 0.2172 | 200 | 2.4639 | 31.1654 | 12.4743 | 27.4006 | 28.9287 | 12.302 |
| 2.3278 | 0.4343 | 400 | 1.7539 | 42.8693 | 20.1924 | 36.1494 | 40.0003 | 16.989 |
| 2.1436 | 0.6515 | 600 | 1.6432 | 44.2597 | 20.9367 | 37.2494 | 41.2059 | 16.7176 |
| 1.9164 | 0.8686 | 800 | 1.5889 | 45.1205 | 22.0337 | 37.8286 | 41.7306 | 16.6687 |
| 1.8284 | 1.0858 | 1000 | 1.5674 | 45.3218 | 22.046 | 38.1683 | 42.0773 | 17.0954 |
| 1.867 | 1.3029 | 1200 | 1.5335 | 46.4108 | 23.0209 | 38.8108 | 42.7552 | 16.5978 |
| 1.9207 | 1.5201 | 1400 | 1.5132 | 46.1874 | 22.5253 | 38.8827 | 42.7655 | 17.2237 |
| 1.7358 | 1.7372 | 1600 | 1.5014 | 46.2941 | 22.9953 | 39.2702 | 42.8078 | 16.1675 |
| 1.7793 | 1.9544 | 1800 | 1.4895 | 46.7817 | 23.1127 | 39.1969 | 43.2426 | 17.3582 |
| 1.5886 | 2.1716 | 2000 | 1.4896 | 47.353 | 24.1783 | 40.2329 | 44.033 | 17.0073 |
| 1.6335 | 2.3887 | 2200 | 1.4818 | 46.7309 | 23.5532 | 39.7803 | 43.3096 | 16.4328 |
| 1.6689 | 2.6059 | 2400 | 1.4659 | 46.9689 | 23.8679 | 39.6689 | 43.5137 | 16.6553 |
| 1.6135 | 2.8230 | 2600 | 1.4577 | 47.0218 | 23.1687 | 39.5868 | 43.4073 | 16.7958 |
| 1.4804 | 3.0402 | 2800 | 1.4596 | 47.1315 | 23.6909 | 39.8844 | 43.5022 | 16.6993 |
| 1.5034 | 3.2573 | 3000 | 1.4608 | 47.3203 | 23.8719 | 40.1168 | 43.7459 | 17.0831 |
| 1.5759 | 3.4745 | 3200 | 1.4518 | 47.3529 | 24.0592 | 40.0045 | 43.7621 | 17.0868 |
| 1.5194 | 3.6916 | 3400 | 1.4493 | 47.4741 | 24.2703 | 40.4503 | 44.1173 | 16.9413 |
| 1.4981 | 3.9088 | 3600 | 1.4462 | 47.4878 | 24.0257 | 40.1823 | 43.9778 | 16.8851 |
| 1.3874 | 4.1260 | 3800 | 1.4446 | 47.3075 | 24.1674 | 40.0633 | 43.8385 | 16.9597 |
| 1.4586 | 4.3431 | 4000 | 1.4418 | 47.4893 | 24.2216 | 40.2151 | 43.8637 | 17.0575 |
| 1.459 | 4.5603 | 4200 | 1.4431 | 47.3265 | 24.2862 | 40.0177 | 43.8328 | 17.0269 |
| 1.5378 | 4.7774 | 4400 | 1.4412 | 47.2638 | 24.1706 | 39.9324 | 43.7584 | 17.066 |
| 1.4544 | 4.9946 | 4600 | 1.4424 | 47.5943 | 24.4996 | 40.2349 | 43.9923 | 17.0342 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
|
0xfaskety/Qwen-Qwen2-1.5B-1719887103 | 0xfaskety | 2024-07-02T02:25:09Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-1.5B",
"region:us"
] | null | 2024-07-02T02:25:03Z | ---
library_name: peft
base_model: Qwen/Qwen2-1.5B
---
# Model Card for Model ID
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### Framework versions
- PEFT 0.11.1 |
habulaj/157266134926 | habulaj | 2024-07-02T02:26:22Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:26:15Z | Entry not found |
habulaj/388509354211 | habulaj | 2024-07-02T02:26:42Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:26:36Z | Entry not found |
houbw/llama38b_ruozhiba_3 | houbw | 2024-07-02T02:28:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-Instruct-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T02:27:32Z | ---
base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** houbw
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
jinwoo1126/distilgpt2-ko | jinwoo1126 | 2024-07-02T02:28:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-02T02:28:07Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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habulaj/2375123442 | habulaj | 2024-07-02T02:30:13Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:30:04Z | Entry not found |
Yuki20/llama3_8b_sql2 | Yuki20 | 2024-07-02T02:32:15Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T02:32:08Z | ---
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** Yuki20
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
maxseats/yeah_tmp | maxseats | 2024-07-02T04:00:03Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-02T02:32:11Z | Entry not found |
albarpambagio/distilbert-base-indonesian-finetuned-PRDECT-ID-cq | albarpambagio | 2024-07-02T02:34:23Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T02:32:19Z | Invalid username or password. |
habulaj/144960132929 | habulaj | 2024-07-02T02:34:02Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:33:59Z | Entry not found |
sameeahameed/mistral-7b-model_lora_model_LMD_updates | sameeahameed | 2024-07-02T02:34:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/mistral-7b-v0.3-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T02:34:08Z | ---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
---
# Uploaded model
- **Developed by:** sameeahameed
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-v0.3-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
Ewopally/my_awesome_swag_model | Ewopally | 2024-07-02T02:34:13Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:34:13Z | Entry not found |
taehyunzzz/switch-base-8-samsum-top-4 | taehyunzzz | 2024-07-02T02:34:22Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:34:22Z | Entry not found |
sameeahameed/mistral-7b-model_lora_model_LMD_updated | sameeahameed | 2024-07-02T02:34:35Z | 0 | 0 | transformers | [
"transformers",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-02T02:34:32Z | ---
library_name: transformers
tags:
- unsloth
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
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## Technical Specifications [optional]
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[More Information Needed]
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MarcelloMatos/llama3-training-coppelia | MarcelloMatos | 2024-07-02T03:19:58Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"sft",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-02T02:35:20Z | ---
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
---
# Uploaded model
- **Developed by:** MarcelloMatos
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
habulaj/263039241793 | habulaj | 2024-07-02T02:36:11Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-02T02:35:57Z | Entry not found |
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