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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Novski/PPO-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-26T17:46:00+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Unclad3610/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-26T17:49:18+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
text-classification | transformers |
<!-- 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. -->
# seq
This model is a fine-tuned version of [autoevaluate/binary-classification](https://huggingface.co/autoevaluate/binary-classi... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "autoevaluate/binary-classification", "model-index": [{"name": "seq", "results": []}]} | qianyihuang1203/seq | null | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:autoevaluate/binary-classification",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T17:49:40+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #text-classification #generated_from_trainer #base_model-autoevaluate/binary-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| seq
===
This model is a fine-tuned version of autoevaluate/binary-classification on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2408
* Accuracy: 0.9352
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
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null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | cesaenv/hojasVid | null | [
"fastai",
"region:us",
"has_space"
] | null | 2024-04-26T17:50:24+00:00 | [] | [] | TAGS
#fastai #region-us #has_space
|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
3. Join the fastai community on the ... | [
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentation here).\n\n3. Join the fastai co... | [
"TAGS\n#fastai #region-us #has_space \n",
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null | null |
# NotAiLOL/Boundary-Coder-Yi-2x9B-MoE-Q4_K_M-GGUF
This model was converted to GGUF format from [`NotAiLOL/Boundary-Coder-Yi-2x9B-MoE`](https://huggingface.co/NotAiLOL/Boundary-Coder-Yi-2x9B-MoE) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [o... | {"license": "apache-2.0", "tags": ["moe", "merge", "mergekit", "01-ai/Yi-9B-200K", "TechxGenus/Yi-9B-Coder", "llama-cpp", "gguf-my-repo"], "base_model": ["01-ai/Yi-9B-200K", "TechxGenus/Yi-9B-Coder"]} | NotAiLOL/Boundary-Coder-Yi-2x9B-MoE-Q4_K_M-GGUF | null | [
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"moe",
"merge",
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"01-ai/Yi-9B-200K",
"TechxGenus/Yi-9B-Coder",
"llama-cpp",
"gguf-my-repo",
"base_model:01-ai/Yi-9B-200K",
"base_model:TechxGenus/Yi-9B-Coder",
"license:apache-2.0",
"region:us"
] | null | 2024-04-26T17:50:47+00:00 | [] | [] | TAGS
#gguf #moe #merge #mergekit #01-ai/Yi-9B-200K #TechxGenus/Yi-9B-Coder #llama-cpp #gguf-my-repo #base_model-01-ai/Yi-9B-200K #base_model-TechxGenus/Yi-9B-Coder #license-apache-2.0 #region-us
|
# NotAiLOL/Boundary-Coder-Yi-2x9B-MoE-Q4_K_M-GGUF
This model was converted to GGUF format from 'NotAiLOL/Boundary-Coder-Yi-2x9B-MoE' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.... | [
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text-classification | transformers |
<!-- 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. -->
# distilbert-base-uncased-finetuned-clinc
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-clinc", "results": []}]} | saqidr/distilbert-base-uncased-finetuned-clinc | null | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T17:51:02+00:00 | [] | [] | TAGS
#transformers #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-clinc
=======================================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8019
* Accuracy: 0.9165
Model description
-----------------
More information nee... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
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image-classification | transformers |
<!-- 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. -->
# Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224-in22k_fold5
This model is a fine-tuned version of [microsoft/swin-large... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swin-large-patch4-window7-224-in22k", "model-index": [{"name": "Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224-in22k_fold5", "results": [{"task": {"type": "image-classif... | onizukal/Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224-in22k_fold5 | null | [
"transformers",
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"autotrain_compatible",
"endpoints_compatible",
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] | null | 2024-04-26T17:51:17+00:00 | [] | [] | TAGS
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| Boya1\_RMSProp\_1-e5\_10Epoch\_swin-large-patch4-window7-224-in22k\_fold5
=========================================================================
This model is a fine-tuned version of microsoft/swin-large-patch4-window7-224-in22k on the imagefolder dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio... | [
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null | transformers |
# Uploaded model
- **Developed by:** cchakons
- **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/... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | cchakons/sv_model_try | null | [
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"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T17:52:54+00:00 | [] | [
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|
# Uploaded model
- Developed by: cchakons
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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text2text-generation | transformers |
<!-- 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. -->
# trans
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the f... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "t5-small", "model-index": [{"name": "trans", "results": []}]} | qianyihuang1203/trans | null | [
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"tensorboard",
"safetensors",
"t5",
"text2text-generation",
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"base_model:t5-small",
"license:apache-2.0",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-26T17:54:14+00:00 | [] | [] | TAGS
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| trans
=====
This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.1920
* Bleu: 0.2223
* Gen Len: 18.1849
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More... | [
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null | peft |
<!-- 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. -->
# GUE_mouse_4-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_4-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_4096_512_27M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T17:55:46+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_4-seqsight\_4096\_512\_27M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5795
* F1 Score: 0.6958
* Accu... | [
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text-generation | transformers | ## KoDolph-2x8b
> **Update @ 2024.04.26:** Linear Merge of [Llama-3-Open-Ko-8B-Instruct-preview](https://huggingface.co/beomi/Llama-3-Open-Ko-8B-Instruct-preview) and [dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b)
### Model Details
**KoDolph-2x8b:**
I had this idea at ni... | {"language": ["en", "ko"], "license": "other", "tags": ["mergekit", "merge", "facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT Meta Llama 3 Version Release Date: ... | asiansoul/KoDolph-2x8b-Instruct | null | [
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| ## KoDolph-2x8b
> Update @ 2024.04.26: Linear Merge of Llama-3-Open-Ko-8B-Instruct-preview and dolphin-2.9-llama3-8b
### Model Details
KoDolph-2x8b:
I had this idea at night that it would make sense to make a Linear Merge
Model Merge:
Linear Merge
### Composition
1. Base Layers from Llama-3-Open-Ko-8B-Instruct-... | [
"## KoDolph-2x8b\n\n> Update @ 2024.04.26: Linear Merge of Llama-3-Open-Ko-8B-Instruct-preview and dolphin-2.9-llama3-8b",
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null | peft |
<!-- 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. -->
# GUE_mouse_4-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_4-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T17:57:13+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_4-seqsight\_4096\_512\_27M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5900
* F1 Score: 0.7031
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | transformers |
# Uploaded model
- **Developed by:** kchopra04
- **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... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "gguf"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | kchopra04/llama3-finetune-saxs-gguf | null | [
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|
# Uploaded model
- Developed by: kchopra04
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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null | peft |
<!-- 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. -->
# GUE_mouse_4-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_4-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T17:57:20+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_4-seqsight\_4096\_512\_27M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6336
* F1 Score: 0.7125
* Ac... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_mouse_3-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_3-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_4096_512_27M-L1_f | null | [
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"generated_from_trainer",
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"region:us"
] | null | 2024-04-26T17:58:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_3-seqsight\_4096\_512\_27M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6345
* F1 Score: 0.7991
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_mouse_3-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_3-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T17:59:06+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_3-seqsight\_4096\_512\_27M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4676
* F1 Score: 0.8326
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_mouse_3-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_3-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_4096_512_27M-L32_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T17:59:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_3-seqsight\_4096\_512\_27M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1748
* F1 Score: 0.8451
* Ac... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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text-generation | null |
## Llamacpp imatrix Quantizations of OpenBioLLM-Llama3-8B
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2717">b2717</a> for quantization.
Original model: https://huggingface.co/aaditya/OpenBioLLM-Llama3-8B
All quants made ... | {"language": ["en"], "license": "llama3", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "meta-llama/Meta-Llama-3-8B", "widget": [{"example_title": "OpenBioLLM-8B", "messages": [{"role": "system", "content": "You are an expert and experien... | nitsuai/OpenBioLLM-Llama3-8B-GGUF | null | [
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] | null | 2024-04-26T18:02:16+00:00 | [] | [
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| Llamacpp imatrix Quantizations of OpenBioLLM-Llama3-8B
------------------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
-------------
No chat template s... | [] | [
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] |
token-classification | transformers |
<!-- 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. -->
# group1_non_all_zero
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "group1_non_all_zero", "results": []}]} | anismahmahi/group1_non_all_zero | null | [
"transformers",
"pytorch",
"tensorboard",
"deberta-v2",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:02:17+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #deberta-v2 #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| group1\_non\_all\_zero
======================
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7437
* Precision: 0.0149
* Recall: 0.1076
* F1: 0.0262
* Accuracy: 0.9260
Model description
-----------------
Mo... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 15",
"### Train... | [
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text-generation | transformers |
# Keiana-L3-Test5.75-8B-13.5
Keiana-L3-Test5.75-8B-13.5 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
# Keep in mind that, this merged model isn't usually tested at the moment, which could benefit in vocabulary error.
*... | {"tags": ["merge", "mergekit", "lazymergekit", "Kaoeiri/Keiana-L3-Test5.4-8B-10", "Undi95/Llama-3-LewdPlay-8B", "Kaoeiri/Keiana-L3-Test4.7-8B-3"], "base_model": ["Kaoeiri/Keiana-L3-Test5.4-8B-10", "Undi95/Llama-3-LewdPlay-8B", "Kaoeiri/Keiana-L3-Test4.7-8B-3"]} | Kaoeiri/Keiana-L3-Test5.75-8B-13.5 | null | [
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"conversational",
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"base_model:Undi95/Llama-3-LewdPl... | null | 2024-04-26T18:02:28+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #merge #mergekit #lazymergekit #Kaoeiri/Keiana-L3-Test5.4-8B-10 #Undi95/Llama-3-LewdPlay-8B #Kaoeiri/Keiana-L3-Test4.7-8B-3 #conversational #base_model-Kaoeiri/Keiana-L3-Test5.4-8B-10 #base_model-Undi95/Llama-3-LewdPlay-8B #base_model-Kaoeiri/Keiana-L3-Test4.7-8B-... |
# Keiana-L3-Test5.75-8B-13.5
Keiana-L3-Test5.75-8B-13.5 is a merge of the following models using LazyMergekit:
# Keep in mind that, this merged model isn't usually tested at the moment, which could benefit in vocabulary error.
* Kaoeiri/Keiana-L3-Test5.4-8B-10
* Undi95/Llama-3-LewdPlay-8B
* Kaoeiri/Keiana-L3-Test4.7... | [
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | orpo-explorers/kaist-mistral-orpo-capybara-beta-0.05-1epoch | null | [
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#transformers #safetensors #mistral #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | null |
## Llamacpp imatrix Quantizations of Llama-3-8B-LexiFun-Uncensored-V1
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2717">b2717</a> for quantization.
Original model: https://huggingface.co/Orenguteng/Llama-3-8B-LexiFun-Unce... | {"language": ["en"], "license": "other", "tags": ["llama3", "comedy", "comedian", "fun", "funny", "llama38b", "laugh", "sarcasm", "roleplay"], "license_name": "llama3", "license_link": "https://llama.meta.com/llama3/license/", "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | nitsuai/Llama-3-8B-LexiFun-Uncensored-V1-GGUF | null | [
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#gguf #llama3 #comedy #comedian #fun #funny #llama38b #laugh #sarcasm #roleplay #text-generation #en #license-other #region-us
| Llamacpp imatrix Quantizations of Llama-3-8B-LexiFun-Uncensored-V1
------------------------------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
----------... | [] | [
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null | peft |
<!-- 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. -->
# GUE_mouse_2-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_2-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_4096_512_27M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:07:09+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_2-seqsight\_4096\_512\_27M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2800
* F1 Score: 0.8689
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_mouse_2-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_2-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:08:05+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_2-seqsight\_4096\_512\_27M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4841
* F1 Score: 0.8841
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_mouse_2-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_mouse_2-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:08:13+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_mouse\_2-seqsight\_4096\_512\_27M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6199
* F1 Score: 0.8993
* Ac... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_splice_reconstructed-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_2... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_4096_512_27M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:09:21+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_splice\_reconstructed-seqsight\_4096\_512\_27M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_splice_reconstructed-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_2... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:09:27+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_splice\_reconstructed-seqsight\_4096\_512\_27M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_splice_reconstructed-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:09:49+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_splice\_reconstructed-seqsight\_4096\_512\_27M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | orpo-explorers/kaist-mistral-orpo-capybara-beta-0.05-2epoch | null | [
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#transformers #safetensors #mistral #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | peft |
<!-- 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. -->
# GUE_tf_0-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_0-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_4096_512_27M-L1_f | null | [
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"safetensors",
"generated_from_trainer",
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"region:us"
] | null | 2024-04-26T18:11:09+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_0-seqsight\_4096\_512\_27M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3628
* F1 Score: 0.8287
* Accuracy: 0.8... | [
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sentence-similarity | sentence-transformers | # # Fast-Inference with Ctranslate2
Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on CPU or GPU.
quantized version of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)
```bash
pip install hf-hub-ctranslate2>=2.12.0 ctranslate2>=3.17.1... | {"language": "en", "license": "apache-2.0", "tags": ["ctranslate2", "int8", "float16", "sentence-transformers", "feature-extraction", "sentence-similarity"], "datasets": ["s2orc", "flax-sentence-embeddings/stackexchange_xml", "ms_marco", "gooaq", "yahoo_answers_topics", "code_search_net", "search_qa", "eli5", "snli", "... | nitsuai/ct2fast-all-MiniLM-L6-v2 | null | [
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"int8",
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"feature-extraction",
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"dataset:ms_marco",
"dataset:gooaq",
"dataset:yahoo_answers_topics",
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"da... | null | 2024-04-26T18:14:40+00:00 | [
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=================================
Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on CPU or GPU.
quantized version of sentence-transformers/all-MiniLM-L6-v2
Checkpoint compatible to ctranslate2>=3.17.1
and hf-hub-ctranslate2>=2.12.0
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null | transformers | '---
pipeline_tag: sentence-similarity
tags:
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- sentence-transformers
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- sentence-similarity
language: en
license: apache-2.0
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- gooaq
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- code_search_net
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- sentence-similarity
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license: apache-2.0
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- eli5
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sentence-similarity | sentence-transformers | # # Fast-Inference with Ctranslate2
Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on CPU or GPU.
quantized version of [sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2)
```bash
pip install hf-h... | {"language": "multilingual", "license": "apache-2.0", "tags": ["ctranslate2", "int8", "float16", "sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | nitsuai/ct2fast-paraphrase-multilingual-MiniLM-L12-v2 | null | [
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| # # Fast-Inference with Ctranslate2
Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on CPU or GPU.
quantized version of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
Checkpoint compatible to ctranslate2>=3.17.1
and hf-hub-ctranslate2>=2.12.0
- 'compute_type=int8_float16' ... | [
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null | peft |
<!-- 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. -->
# GUE_tf_0-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_0-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:17:38+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_0-seqsight\_4096\_512\_27M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3647
* F1 Score: 0.8277
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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image-classification | transformers |
<!-- 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. -->
# dog-or-food-arturo-guerrero
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/goo... | {"license": "apache-2.0", "tags": ["image-clasification", "generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "dog-or-food-arturo-guerrero", "results": []}]} | arturoxdev/dog-or-food-arturo-guerrero | null | [
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"tensorboard",
"vit",
"image-classification",
"image-clasification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:18:01+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #image-clasification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| dog-or-food-arturo-guerrero
===========================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the lewtun/dog\_food dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0048
* Accuracy: 0.9987
Model description
-----------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 4",
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null | peft |
<!-- 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. -->
# GUE_tf_0-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_0-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:18:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_0-seqsight\_4096\_512\_27M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3656
* F1 Score: 0.8327
* Accuracy: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_tf_1-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_1-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_4096_512_27M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_1-seqsight\_4096\_512\_27M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3351
* F1 Score: 0.8588
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | null |
<!-- 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. -->
# Mistral-7B-Instruct-v0.2-absa-MT-laptops
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "Mistral-7B-Instruct-v0.2-absa-MT-laptops", "results": []}]} | Shakhovak/Mistral-7B-Instruct-v0.2-absa-MT-laptops | null | [
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-26T18:18:42+00:00 | [] | [] | TAGS
#generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
| Mistral-7B-Instruct-v0.2-absa-MT-laptops
========================================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0060
Model description
-----------------
More information needed
In... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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text-generation | transformers |
# Keiana-L3-Test5.8-8B-14
Keiana-L3-Test5.8-8B-14 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
# Keep in mind that, this merged model isn't usually tested at the moment, which could benefit in vocabulary error.
* [Kaoe... | {"tags": ["merge", "mergekit", "lazymergekit", "Kaoeiri/Keiana-L3-Test5.4-8B-10", "Undi95/Llama-3-LewdPlay-8B", "Kaoeiri/Keiana-L3-Test4.7-8B-3"], "base_model": ["Kaoeiri/Keiana-L3-Test5.4-8B-10", "Undi95/Llama-3-LewdPlay-8B", "Kaoeiri/Keiana-L3-Test4.7-8B-3"]} | Kaoeiri/Keiana-L3-Test5.8-8B-14 | null | [
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"text-generation",
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"conversational",
"base_model:Kaoeiri/Keiana-L3-Test5.4-8B-10",
"base_model:Undi95/Llama-3-LewdPl... | null | 2024-04-26T18:18:52+00:00 | [] | [] | TAGS
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# Keiana-L3-Test5.8-8B-14
Keiana-L3-Test5.8-8B-14 is a merge of the following models using LazyMergekit:
# Keep in mind that, this merged model isn't usually tested at the moment, which could benefit in vocabulary error.
* Kaoeiri/Keiana-L3-Test5.4-8B-10
* Undi95/Llama-3-LewdPlay-8B
* Kaoeiri/Keiana-L3-Test4.7-8B-3
... | [
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | CMU-AIR2/math-deepseek-FULL-ArithHardC11 | null | [
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"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-26T18:21:08+00:00 | [
"1910.09700"
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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token-classification | transformers |
<!-- 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. -->
# group4_non_all_zero
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "group4_non_all_zero", "results": []}]} | anismahmahi/group4_non_all_zero | null | [
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"deberta-v2",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:21:13+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #deberta-v2 #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| group4\_non\_all\_zero
======================
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2820
* Precision: 0.0006
* Recall: 0.08
* F1: 0.0012
* Accuracy: 0.4380
Model description
-----------------
More... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 15",
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null | transformers |
# acidsound/Bllossom-Q4_K_M-GGUF
This model was converted to GGUF format from [`MLP-KTLim/Bllossom`](https://huggingface.co/MLP-KTLim/Bllossom) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/MLP-KTLi... | {"language": ["en", "ko"], "license": "apache-2.0", "library_name": "transformers", "tags": ["llama-cpp", "gguf-my-repo"], "base_model": ["meta-llama/Meta-Llama-3-8B"]} | acidsound/Bllossom-Q4_K_M-GGUF | null | [
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"base_model:meta-llama/Meta-Llama-3-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:22:26+00:00 | [] | [
"en",
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] | TAGS
#transformers #gguf #llama-cpp #gguf-my-repo #en #ko #base_model-meta-llama/Meta-Llama-3-8B #license-apache-2.0 #endpoints_compatible #region-us
|
# acidsound/Bllossom-Q4_K_M-GGUF
This model was converted to GGUF format from 'MLP-KTLim/Bllossom' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
Note: You can... | [
"# acidsound/Bllossom-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'MLP-KTLim/Bllossom' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
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"# acidsound/Bllossom-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'MLP-KTLim/Bllossom' using URL via the URL's GGUF-my-repo space.\nRefer to th... | [
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null | peft |
<!-- 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. -->
# GUE_tf_1-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_1-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:22:34+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_1-seqsight\_4096\_512\_27M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3286
* F1 Score: 0.8679
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [ResplendentAI/Aura_Uncensored_l3_8B](https://huggingface.co/Resplen... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["ResplendentAI/Aura_Uncensored_l3_8B", "vicgalle/Roleplay-Llama-3-8B", "Undi95/Llama-3-LewdPlay-8B-evo", "abhishek/autotrain-llama3-orpo"]} | Azazelle/Llama-3-8B-contaminated-roleplay | null | [
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"base_model:Undi95/Llama-3-LewdPlay-8B-evo",
"base_model:abhishek/autotrain-llama3-... | null | 2024-04-26T18:23:03+00:00 | [
"2403.19522"
] | [] | TAGS
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This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the Model Stock merge method using ResplendentAI/Aura_Uncensored_l3_8B as a base.
### Models Merged
The following models were included in the merge:
* vicgalle/Roleplay-Llama... | [
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question-answering | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# AlessandraAbreu/ftllm_loggi
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbe... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "AlessandraAbreu/ftllm_loggi", "results": []}]} | AlessandraAbreu/ftllm_loggi | null | [
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"base_model:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:24:09+00:00 | [] | [] | TAGS
#transformers #tf #distilbert #question-answering #generated_from_keras_callback #base_model-distilbert/distilbert-base-uncased #license-apache-2.0 #endpoints_compatible #region-us
| AlessandraAbreu/ftllm\_loggi
============================
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 1.9755
* Validation Loss: 1.9604
* Epoch: 1
Model description
-----------------
More in... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'weight\\_decay': None, 'clipnorm': None, 'global\\_clipnorm': None, 'clipvalue': None, 'use\\_ema': False, 'ema\\_momentum': 0.99, 'ema\\_overwrite\\_frequency': None, 'jit\\_compile': Tru... | [
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text2text-generation | transformers |
<!-- 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. -->
# my_awesome_billsum_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "t5-small", "model-index": [{"name": "my_awesome_billsum_model", "results": []}]} | josiahgottfried/my_awesome_billsum_model | null | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:t5-small",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-26T18:25:30+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-t5-small #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| my\_awesome\_billsum\_model
===========================
This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.4539
* Rouge1: 0.1468
* Rouge2: 0.0569
* Rougel: 0.1209
* Rougelsum: 0.1212
* Gen Len: 19.0
Model description
-----------... | [
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text-generation | transformers |
# Qwen1.5-110B-Chat
## About Quantization
我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行GPTQ量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
We use the modelscope [swift](https://github.com/modelscope/swift/) reposit... | {"language": ["en"], "license": "other", "tags": ["chat", "qwen", "gptq", "int8", "8bits", "110b"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation"} | study-hjt/Qwen1.5-110B-Chat-GPTQ-Int8 | null | [
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|
# Qwen1.5-110B-Chat
## About Quantization
我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:
We use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:
## Introduction
Qwen1.5 is the beta version of Qwen2, a transf... | [
"# Qwen1.5-110B-Chat",
"## About Quantization\n我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:\n\nWe use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:",
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null | 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]:** ... | {"library_name": "peft", "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | Hajas0/hun_emotion_modification | null | [
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### Model Sources [optional]
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null | peft |
<!-- 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. -->
# GUE_tf_1-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_1-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_4096_512_27M-L32_f | null | [
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| GUE\_tf\_1-seqsight\_4096\_512\_27M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3607
* F1 Score: 0.8438
* Accuracy: 0... | [
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | nem012/gemma2B-r16MHCv2 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
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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- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | peft |
<!-- 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. -->
# GUE_tf_4-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_4-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_4096_512_27M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_4-seqsight\_4096\_512\_27M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3500
* F1 Score: 0.8474
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- 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. -->
# GUE_tf_4-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_4-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_4096_512_27M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_4-seqsight\_4096\_512\_27M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3638
* F1 Score: 0.8528
* Accuracy: 0.8... | [
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text-generation | transformers |
# Qwen1.5-32B-Chat
## About Quantization
我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行GPTQ量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
We use the modelscope [swift](https://github.com/modelscope/swift/) reposito... | {"language": ["en", "zh"], "license": "other", "tags": ["qwen", "32b", "gptq", "int8", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-32B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation"} | study-hjt/Qwen1.5-32B-Chat-GPTQ-Int8 | null | [
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|
# Qwen1.5-32B-Chat
## About Quantization
我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:
We use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:
## Introduction
Qwen1.5 is the beta version of Qwen2, a transform... | [
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": ["llama-factory"]} | zilongpa/aes-llama3-v1 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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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text-to-image | diffusers |
<!-- 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. -->
# Critical Dream - cosmicBboy/stable-diffusion-xl-base-1.0-lora-dreambooth-critdream-v0.7.2
<Gallery />
## Model descrip... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora", "template:sd-lora"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "prompt": "a picture of [dm-matt-mercer], a dungeon master. backgr... | cosmicBboy/stable-diffusion-xl-base-1.0-lora-dreambooth-critdream-v0.7.2 | null | [
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] | null | 2024-04-26T18:33:21+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion-xl #stable-diffusion-xl-diffusers #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# Critical Dream - cosmicBboy/stable-diffusion-xl-base-1.0-lora-dreambooth-critdream-v0.7.2
<Gallery />
## Model description
These are cosmicBboy/stable-diffusion-xl-base-1.0-lora-dreambooth-critdream-v0.7.2 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0, for the purposes of
generating images... | [
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"## Model description\n\nThese are cosmicBboy/stable-diffusion-xl-base-1.0-lora-dreambooth-critdream-v0.7.2 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0, for the purposes of\ngenerat... | [
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"# Critical Dream - cosmicBboy/stable-diffusion-xl-base-1.0-lora-dreambooth-critdream-v0.7.2\n\n<Gallery />",
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null | peft |
<!-- 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. -->
# GUE_tf_4-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_4-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:33:27+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_4-seqsight\_4096\_512\_27M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5227
* F1 Score: 0.8399
* Accuracy: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | null |
<!-- 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. -->
# idefics2-8b-docvqa-finetuned-tutorial
This model is a fine-tuned version of [HuggingFaceM4/idefics2-8b](https://huggingface.co/H... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "HuggingFaceM4/idefics2-8b", "model-index": [{"name": "idefics2-8b-docvqa-finetuned-tutorial", "results": []}]} | GoHugo/idefics2-8b-docvqa-finetuned-tutorial | null | [
"safetensors",
"generated_from_trainer",
"base_model:HuggingFaceM4/idefics2-8b",
"license:apache-2.0",
"region:us"
] | null | 2024-04-26T18:33:43+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-HuggingFaceM4/idefics2-8b #license-apache-2.0 #region-us
|
# idefics2-8b-docvqa-finetuned-tutorial
This model is a fine-tuned version of HuggingFaceM4/idefics2-8b on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# idefics2-8b-docvqa-finetuned-tutorial\n\nThis model is a fine-tuned version of HuggingFaceM4/idefics2-8b on an unknown dataset.",
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"... | [
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text-classification | transformers |
<!-- 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. -->
# bert-finetuned-sem_eval-english
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-finetuned-sem_eval-english", "results": []}]} | Kelvin950/bert-finetuned-sem_eval-english | null | [
"transformers",
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"text-classification",
"generated_from_trainer",
"base_model:bert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:34:24+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-finetuned-sem\_eval-english
================================
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: nan
* F1: 0.0
* Roc Auc: 0.5
* Accuracy: 0.0158
Model description
-----------------
More information n... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
"### Training... | [
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text-generation | transformers |
<!-- 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. -->
# kaist-mistral-orpo-capybara-beta0.05-1epoch-ohp-15k-strat-1-beta0.2-2epoch
This model is a fine-tuned version of [orpo-explorers... | {"tags": ["alignment-handbook", "trl", "orpo", "generated_from_trainer", "trl", "orpo", "generated_from_trainer"], "datasets": ["orpo-explorers/OHP-15k-Stratified-1"], "base_model": "orpo-explorers/kaist-mistral-orpo-capybara-beta-0.05-1epoch", "model-index": [{"name": "kaist-mistral-orpo-capybara-beta0.05-1epoch-ohp-1... | orpo-explorers/kaist-mistral-orpo-capybara-beta0.05-1epoch-ohp-15k-strat-1-beta0.2-2epoch | null | [
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"base_model:orpo-explorers/kaist-mistral-orpo-capybara-beta-0.05-1epoch",
"autotrain_com... | null | 2024-04-26T18:35:00+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #mistral #text-generation #alignment-handbook #trl #orpo #generated_from_trainer #conversational #dataset-orpo-explorers/OHP-15k-Stratified-1 #base_model-orpo-explorers/kaist-mistral-orpo-capybara-beta-0.05-1epoch #autotrain_compatible #endpoints_compatible #text-generation-... |
# kaist-mistral-orpo-capybara-beta0.05-1epoch-ohp-15k-strat-1-beta0.2-2epoch
This model is a fine-tuned version of orpo-explorers/kaist-mistral-orpo-capybara-beta-0.05-1epoch on the orpo-explorers/OHP-15k-Stratified-1 dataset.
## Model description
More information needed
## Intended uses & limitations
More info... | [
"# kaist-mistral-orpo-capybara-beta0.05-1epoch-ohp-15k-strat-1-beta0.2-2epoch\n\nThis model is a fine-tuned version of orpo-explorers/kaist-mistral-orpo-capybara-beta-0.05-1epoch on the orpo-explorers/OHP-15k-Stratified-1 dataset.",
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text-generation | transformers |
# Model Card for Model ID
Fine-tuning for CS5242 project
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [DreamOnRain]
- **Finetuned from model [optional]:** state-spaces/mamba-1.4b-hf
### Model Sources [optional]
<!-- Provide the basic links ... | {"library_name": "transformers", "tags": []} | DreamOnRain/mamba-1.4b-msmath | null | [
"transformers",
"safetensors",
"mamba",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:35:13+00:00 | [] | [] | TAGS
#transformers #safetensors #mamba #text-generation #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
Fine-tuning for CS5242 project
## Model Details
### Model Description
- Developed by: [DreamOnRain]
- Finetuned from model [optional]: state-spaces/mamba-1.4b-hf
### Model Sources [optional]
- Repository: URL
## Training Details
### Training Data
URL
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text2text-generation | transformers |
<!-- 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. -->
# flan-t5-base-eLife
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/flan-t5-base", "model-index": [{"name": "flan-t5-base-eLife", "results": []}]} | Veera007/flan-t5-base-eLife | null | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
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"base_model:google/flan-t5-base",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-26T18:38:03+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-google/flan-t5-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| flan-t5-base-eLife
==================
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0533
* Rouge1: 16.8601
* Rouge2: 3.5043
* Rougel: 13.0262
* Rougelsum: 15.2504
* Gen Len: 19.0
Model description
---------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
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null | peft |
<!-- 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. -->
# GUE_tf_3-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_3-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_4096_512_27M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:39:28+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_3-seqsight\_4096\_512\_27M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5534
* F1 Score: 0.7083
* Accuracy: 0.7... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_tf_3-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_3-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:40:00+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_3-seqsight\_4096\_512\_27M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5302
* F1 Score: 0.7378
* Accuracy: 0.7... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- 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. -->
# GUE_tf_3-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_3-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:40:15+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_3-seqsight\_4096\_512\_27M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5757
* F1 Score: 0.7160
* Accuracy: 0... | [
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null | 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]:** ... | {"library_name": "peft", "base_model": "meta-llama/Meta-Llama-3-8B"} | yiyic/llama-text-entprop-lora-clf-epoch-2 | null | [
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null | 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]
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- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "meta-llama/Meta-Llama-3-8B"} | yiyic/llama-text-prop-lora-clf-epoch-2 | null | [
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null | 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]
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null | peft |
<!-- 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. -->
# GUE_tf_2-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_2-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_4096_512_27M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_2-seqsight\_4096\_512\_27M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4392
* F1 Score: 0.8006
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- 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. -->
# GUE_tf_2-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_2-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_4096_512_27M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_2-seqsight\_4096\_512\_27M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4357
* F1 Score: 0.7959
* Accuracy: 0.7... | [
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null | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | la-min/GENI_GPT | null | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | lexkarlo/dqn-SpaceInvadersNoFrameskip-v4 | null | [
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#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
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and the RL Zoo.
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null | peft |
<!-- 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. -->
# GUE_tf_2-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_2-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_4096_512_27M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_2-seqsight\_4096\_512\_27M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4479
* F1 Score: 0.7913
* Accuracy: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | null |
# Model Card for NeuralTranslate
<!-- Provide a quick summary of what the model is/does. -->
THIS MODEL USES CHATML TEMPLATE!! BE CAREFUL OR YOU MIGHT FIND UNEXPECTED BEHAVIOURS.
This is the secon... | {"language": ["en", "es"], "license": "mit", "tags": ["Translation", "Mistral", "English", "Spanish"], "datasets": ["Thermostatic/ShareGPT_NeuralTranslate_v0.1"]} | Thermostatic/NeuralTranslate_v0.2_GGUF | null | [
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|
!image/png
# Model Card for NeuralTranslate
THIS MODEL USES CHATML TEMPLATE!! BE CAREFUL OR YOU MIGHT FIND UNEXPECTED BEHAVIOURS.
This is the second alpha version of NeuralTranslate. This alpha version doesn't contain overfitting (or at least that's what I think), so no unexpected behaviour should happen and Mist... | [
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | OwOOwO/final5 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
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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- Funded by [optional]:
- Shared by [optional]:
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null | peft |
<!-- 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. -->
# GUE_virus_covid-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_virus_covid-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_4096_512_27M-L1_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:44:31+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_virus\_covid-seqsight\_4096\_512\_27M-L1\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6408
* F1 Score: 0... | [
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... | [
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null | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | akankshya107/llava_dpt_2 | null | [
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"1910.09700"
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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null | peft |
<!-- 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. -->
# gemma2b-dolly15k-r128
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unkn... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "google/gemma-2b", "model-index": [{"name": "gemma2b-dolly15k-r128", "results": []}]} | AlexxxSem/gemma2b-dolly15k-r128 | null | [
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|
# gemma2b-dolly15k-r128
This model is a fine-tuned version of google/gemma-2b on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/n00854180t/ErisMaidFlame-7B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "n00854180t/ErisMaidFlame-7B", "quantized_by": "mradermacher"} | mradermacher/ErisMaidFlame-7B-GGUF | null | [
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#transformers #gguf #mergekit #merge #en #base_model-n00854180t/ErisMaidFlame-7B #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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text-generation | transformers |
# Qwen1.5-110B-Chat
## About Quantization
我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行GPTQ量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
We use the modelscope [swift](https://github.com/modelscope/swift/) reposit... | {"language": ["en"], "license": "other", "tags": ["chat", "qwen", "gptq", "int4", "4bits", "110b"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation"} | study-hjt/Qwen1.5-110B-Chat-GPTQ-Int4 | null | [
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"text-generation",
"chat",
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"conversational",
"en",
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|
# Qwen1.5-110B-Chat
## About Quantization
我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:
We use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:
## Introduction
Qwen1.5 is the beta version of Qwen2, a transfo... | [
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text-generation | transformers |
# 🚀 Skyro-4X8B
Skyro-4X8B is a Mixure of Experts (MoE) made with the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
* [abacusai/Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B)
* [cognitivecomputations/d... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "moe", "frankenmoe", "abacusai/Llama-3-Smaug-8B", "cognitivecomputations/dolphin-2.9-llama3-8b", "Weyaxi/Einstein-v6.1-Llama3-8B", "dreamgen-preview/opus-v1.2-llama-3-8b-base-run3.4-epoch2"], "base_model": ["abacusai/Llama-3-Smaug-8B", "cognitivecomputations/dolph... | saucam/Skyro-4X8B | null | [
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"dreamgen-preview/opus-v1.2-llama-3-8b-base-run3.4-epoch2",
"base_model:abacusa... | null | 2024-04-26T18:50:44+00:00 | [] | [] | TAGS
#transformers #safetensors #mixtral #text-generation #merge #mergekit #moe #frankenmoe #abacusai/Llama-3-Smaug-8B #cognitivecomputations/dolphin-2.9-llama3-8b #Weyaxi/Einstein-v6.1-Llama3-8B #dreamgen-preview/opus-v1.2-llama-3-8b-base-run3.4-epoch2 #base_model-abacusai/Llama-3-Smaug-8B #base_model-cognitivecomputa... |
 made with the following models using Mergekit:
* abacusai/Llama-3-Smaug-8B
* cognitivecomputations/dolphin-2.9-llama3-8b
* Weyaxi/Einstein-v6.1-Llama3-8B
* dreamgen-preview/opus-v1.2-llama-3-8b-base-run3.4-epoch2
## Configuration
## Usage
## Samp... | [
"# Skyro-4X8B\nSkyro-4X8B is a Mixure of Experts (MoE) made with the following models using Mergekit:\n\n* abacusai/Llama-3-Smaug-8B\n* cognitivecomputations/dolphin-2.9-llama3-8b\n* Weyaxi/Einstein-v6.1-Llama3-8B\n* dreamgen-preview/opus-v1.2-llama-3-8b-base-run3.4-epoch2",
"## Configuration",
"## Usage",
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null | peft |
<!-- 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. -->
# GUE_virus_covid-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_virus_covid-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:50:52+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_virus\_covid-seqsight\_4096\_512\_27M-L8\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3185
* F1 Score: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- 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. -->
# GUE_virus_covid-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_virus_covid-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-26T18:51:05+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_virus\_covid-seqsight\_4096\_512\_27M-L32\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0120
* F1 Score:... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- 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. -->
# GUE_prom_prom_300_tata-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_4096_512_46M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-26T18:51:20+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_4096\_512\_46M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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feature-extraction | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | stvhuang/rcr-run-5pqr6lwp-90396-master-0_20240402T105012-ep35 | null | [
"transformers",
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"endpoints_compatible",
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|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/aaditya/OpenBioLLM-Llama3-8B
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/OpenBioLLM-L... | {"language": ["en"], "license": "llama3", "library_name": "transformers", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "aaditya/OpenBioLLM-Llama3-8B", "quantized_by": "mradermacher"} | mradermacher/OpenBioLLM-Llama3-8B-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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] |
null | peft |
<!-- 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. -->
# GUE_prom_prom_300_tata-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_4096_512_46M-L8_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-26T18:52:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_4096\_512\_46M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
*... | [
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null | peft |
<!-- 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. -->
# GUE_prom_prom_300_tata-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_4096_512_46M-L32_f | null | [
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"generated_from_trainer",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_4096\_512\_46M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
... | [
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null | peft |
<!-- 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. -->
# GUE_prom_prom_300_notata-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_4096_512_46M-L1_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_4096\_512\_46M-L1\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation se... | [
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text-generation | transformers |
# CodeQwen1.5-7B-Chat
## About Quantization
我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行GPTQ量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
We use the modelscope [swift](https://github.com/modelscope/swift/) repos... | {"language": ["en"], "license": "other", "tags": ["codeqwen", "code", "chat", "gptq", "int4"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "studios": ["qwen/CodeQwen1.5-7b-Chat-demo"]} | study-hjt/CodeQwen1.5-7B-Chat-GPTQ-Int4 | null | [
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"conversational",
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"license:other",
"autotrain_compatible",
"endpoints_compatible",
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"4-bit",
"region:us"
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|
# CodeQwen1.5-7B-Chat
## About Quantization
我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:
We use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:
## Introduction
CodeQwen1.5 is the Code-Specific version of Qw... | [
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null | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | HenryCai1129/adapter-llama-adapterhappy2sad-1k-50-0.003 | null | [
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"safetensors",
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|
# Model Card for Model ID
## Model Details
### Model Description
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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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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null | 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]:** ... | {"library_name": "peft", "base_model": "mistralai/Mistral-7B-Instruct-v0.2"} | sahanes/Enlighten_Instruct | null | [
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## Model Details
### Model Description
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text-generation | transformers |
# CodeQwen1.5-7B-Chat
## About Quantization
我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行GPTQ量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
We use the modelscope [swift](https://github.com/modelscope/swift/) repos... | {"language": ["en"], "license": "other", "tags": ["chat", "gptq", "codeqwen", "int8"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "studios": ["qwen/CodeQwen1.5-7b-Chat-demo"]} | study-hjt/CodeQwen1.5-7B-Chat-GPTQ-Int8 | null | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"gptq",
"codeqwen",
"int8",
"conversational",
"en",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"8-bit",
"region:us"
] | null | 2024-04-26T18:55:52+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #chat #gptq #codeqwen #int8 #conversational #en #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
|
# CodeQwen1.5-7B-Chat
## About Quantization
我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:
We use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:
## Introduction
CodeQwen1.5 is the Code-Specific version of Qw... | [
"# CodeQwen1.5-7B-Chat",
"## About Quantization\n我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:\n\nWe use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:",
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image-classification | transformers |
<!-- 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. -->
# Action_Classification
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vi... | {"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "Action_Classification", "results": [{"task": {"type": "image-classification", "name": "Image Classifica... | Raihan004/Action_Classification | null | [
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"license:apache-2.0",
"model-index",
"autotrain_compatible",
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] | null | 2024-04-26T18:56:34+00:00 | [] | [] | TAGS
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| Action\_Classification
======================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the agent\_action\_class dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8482
* Accuracy: 0.7629
* Confusion Matrix: [[45, 5, 20, 4, 2, 6, 4, 8, 3, 3], [5, 154, 4, 2, ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 15",
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text-classification | transformers |
<!-- 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. -->
# distilbert-rotten_tomatoes
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-bas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-rotten_tomatoes", "results": []}]} | huiang/distilbert-rotten_tomatoes | null | [
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"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-26T18:58:07+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# distilbert-rotten_tomatoes
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyp... | [
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | shallow6414/mp5d4if | null | [
"transformers",
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"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-26T18:58:09+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
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text-generation | transformers |
# Uploaded model
- **Developed by:** kchopra04
- **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/unslotha... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-Instruct-bnb-4bit"} | kchopra04/lora_model_inst | null | [
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|
# Uploaded model
- Developed by: kchopra04
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
"# Uploaded model\n\n- Developed by: kchopra04\n- License: apache-2.0\n- Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit\n\nThis llama model was trained 2x faster with Unsloth and Huggingface's TRL library.\n\n<img src=\"URL width=\"200\"/>"
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null | peft |
<!-- 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. -->
# run
This model is a fine-tuned version of [salangarica/BioMistral-LLM](https://huggingface.co/salangarica/BioMistral-LLM) on the... | {"library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "salangarica/BioMistral-LLM", "model-index": [{"name": "run", "results": []}]} | salangarica/run | null | [
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"safetensors",
"trl",
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"generated_from_trainer",
"base_model:salangarica/BioMistral-LLM",
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] | null | 2024-04-26T18:59:08+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-salangarica/BioMistral-LLM #region-us
| run
===
This model is a fine-tuned version of salangarica/BioMistral-LLM on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3032
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_ratio... | [
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null | peft | prompt
```
<original>Ok. What do the drivers look like?</original>
<translate to="th">
```
response
```
<original>กรุงเทพอยู่ที่ไหน</original>
<translate to="en">where is bangkok</translate><eos>
```
code to create dataset
```python
import random
alpaca_prompt = """<original>{}</original>
<translate to="{}">{}"""
... | {"library_name": "peft", "base_model": "unsloth/gemma-7b-bnb-4bit"} | ping98k/gemma-7b-translator-0.3-lora | null | [
"peft",
"safetensors",
"base_model:unsloth/gemma-7b-bnb-4bit",
"region:us"
] | null | 2024-04-26T19:06:13+00:00 | [] | [] | TAGS
#peft #safetensors #base_model-unsloth/gemma-7b-bnb-4bit #region-us
| prompt
response
code to create dataset
### Framework versions
- PEFT 0.10.0 | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** kchopra04
- **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/unslotha... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-Instruct-bnb-4bit"} | kchopra04/llama3-inst-finetuned-saxs | null | [
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|
# Uploaded model
- Developed by: kchopra04
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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] | [
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null | null |
# Ognoexperiment27multi_verse_modelMeliodas-7B
Ognoexperiment27multi_verse_modelMeliodas-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: automerger/Ognoexperim... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/Ognoexperiment27multi_verse_modelMeliodas-7B | null | [
"merge",
"mergekit",
"lazymergekit",
"automerger",
"license:apache-2.0",
"region:us"
] | null | 2024-04-26T19:07:40+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #license-apache-2.0 #region-us
|
# Ognoexperiment27multi_verse_modelMeliodas-7B
Ognoexperiment27multi_verse_modelMeliodas-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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] |
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