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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": []} | Mandanaf/llama-SAPS-1 | 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-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | {"language": ["multilingual"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["generation", "question answering", "instruction tuning"], "datasets": ["MBZUAI/Bactrian-X"], "pipeline_tag": "text-generation"} | MaLA-LM/lucky52-bloom-7b1-no-45 | null | [
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|
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
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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": []} | sezenkarakus/image-GIT-event-model-v4 | null | [
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"arxiv:1910.09700",
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"1910.09700"
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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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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": []} | Giuseppe23/mistral_7b_athlos_v0.2 | null | [
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
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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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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="JKUJhonny/q-FrozenLake-v1-with-seed", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_sli... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-with-seed", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "... | JKUJhonny/q-FrozenLake-v1-with-seed | null | [
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#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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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": []} | hgnoi/fine-tune-0 | null | [
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"autotrain_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:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | {"language": ["multilingual"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["generation", "question answering", "instruction tuning"], "datasets": ["MBZUAI/Bactrian-X"], "pipeline_tag": "text-generation"} | MaLA-LM/lucky52-bloom-7b1-no-46 | null | [
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### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
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text-classification | transformers |
## Overview
Zalmati is a powerful multilingual language model trained on the massive and diverse PetraAI dataset. It can handle a wide range of natural language processing tasks including text classification, emotion analysis, question answering, translation, summarization, text generation and more across multiple do... | {"language": ["ar", "en"], "license": "apache-2.0", "tags": ["chemistry", "biology", "finance", "legal", "music", "code", "art", "climate", "medical", "text-classification", "emotion", "endpoints-template"], "datasets": ["microsoft/orca-math-word-problems-200k", "Cohere/wikipedia-2023-11-embed-multilingual-v3", "Huggin... | PetraAI/Zalmati | null | [
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text-generation | null | GGUFs for Pygmalion 2 13b - https://huggingface.co/upro/pygmalion-2-13b
iMatrix GGUFs generated with Kalomaze's semi-random groups_merged.txt | {"language": ["en"], "license": "llama2", "tags": ["text generation", "instruct"], "datasets": ["PygmalionAI/PIPPA", "Open-Orca/OpenOrca", "Norquinal/claude_multiround_chat_30k", "jondurbin/airoboros-gpt4-1.4.1", "databricks/databricks-dolly-15k"], "pipeline_tag": "text-generation", "inference": false} | MarsupialAI/Pygmalion-2-13b_iMatrix_GGUF | null | [
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reinforcement-learning | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Docum... | {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | Gonke/poca-SoccerTwos | null | [
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"onnx",
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#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us
|
# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* ... | [
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text-classification | 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": []} | KGsteven/0404personnel_and_safety_related_labels | null | [
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"roberta",
"text-classification",
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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]:
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text-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
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### Model Description
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summarization | 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": ["summarization"], "pipeline_tag": "summarization"} | BeenaSamuel/t5_cnn_daily_mail_abstractive_summarizer | null | [
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"arxiv:1910.09700",
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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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image-classification | transformers |
# Model Card for Model ID
This model identifies pneumonia in chest x-ray images
In the "Inference API" interface on this page:
- LABEL_0 is a NORMAL result
- LABEL_1 is a positive result for PNEUMONIA
| {"library_name": "transformers", "tags": []} | Borjamg/pneumonia_model | null | [
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# Model Card for Model ID
This model identifies pneumonia in chest x-ray images
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audio-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. -->
# distilhubert-finetuned-gtzan
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/disti... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["marsyas/gtzan"], "metrics": ["accuracy"], "base_model": "ntu-spml/distilhubert", "model-index": [{"name": "distilhubert-finetuned-gtzan", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"name":... | homerquan/distilhubert-finetuned-gtzan | null | [
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| distilhubert-finetuned-gtzan
============================
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6468
* Accuracy: 0.83
Model description
-----------------
More information needed
Intended uses & limit... | [
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text-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | {"language": ["multilingual"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["generation", "question answering", "instruction tuning"], "datasets": ["MBZUAI/Bactrian-X"], "pipeline_tag": "text-generation"} | MaLA-LM/lucky52-bloom-7b1-no-48 | null | [
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|
### Model Description
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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. -->
# logs
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the foll... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "t5-small", "model-index": [{"name": "logs", "results": []}]} | BeenaSamuel/logs | null | [
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|
# logs
This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3006
- eval_rouge1: 0.5924
- eval_rouge2: 0.326
- eval_rougeL: 0.5425
- eval_gen_len: 82.8793
- eval_runtime: 174.5683
- eval_samples_per_second: 6.124
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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. -->
# vit5-base-transcript-summarizer
This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "VietAI/vit5-base", "model-index": [{"name": "vit5-base-transcript-summarizer", "results": []}]} | chamdentimem/vit5-base-transcript-summarizer | null | [
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| vit5-base-transcript-summarizer
===============================
This model is a fine-tuned version of VietAI/vit5-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5995
* Rouge1: 52.1518
* Rouge2: 28.7254
* Rougel: 41.1877
* Rougelsum: 46.0726
* Gen Len: 16.5342
Model de... | [
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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... | marmeladenaal/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-04T14:51:59+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-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. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axo... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mixtral-8x7B-v0.1", "model-index": [{"name": "out", "results": []}]} | KolaGang/Red_Panda | null | [
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"base_model:mistralai/Mixtral-8x7B-v0.1",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-04T14:52:21+00:00 | [] | [] | TAGS
#transformers #safetensors #mixtral #text-generation #generated_from_trainer #base_model-mistralai/Mixtral-8x7B-v0.1 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<img src="URL alt="Built with Axolotl" width="200" height="32"/>
<details><summary>See axolotl config</summary>
axolotl version: '0.4.0'
</details><br>
# out
This model is a fine-tuned version of mistralai/Mixtral-8x7B-v0.1 on the None dataset.
## Model description
More information needed
## Intended uses & ... | [
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"## Training procedure",
"### Tra... | [
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token-classification | 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": []} | Rishihesaan/TamilNER | null | [
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"albert",
"token-classification",
"arxiv:1910.09700",
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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. -->
# coref-mem-base-full
This model is a fine-tuned version of [eddieman78/coref-mem-base-full](https://huggingface.co/eddieman78/cor... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "eddieman78/coref-mem-base-full", "model-index": [{"name": "coref-mem-base-full", "results": []}]} | eddieman78/coref-mem-base-full | null | [
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| coref-mem-base-full
===================
This model is a fine-tuned version of eddieman78/coref-mem-base-full on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0085
Model description
-----------------
More information needed
Intended uses & limitations
--------------------... | [
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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. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axo... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mixtral-8x7B-v0.1", "model-index": [{"name": "qlora-out", "results": []}]} | KolaGang/scary_panda | null | [
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|
<img src="URL alt="Built with Axolotl" width="200" height="32"/>
<details><summary>See axolotl config</summary>
axolotl version: '0.4.0'
</details><br>
# qlora-out
This model is a fine-tuned version of mistralai/Mixtral-8x7B-v0.1 on the None dataset.
## Model description
More information needed
## Intended u... | [
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text-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | {"language": ["multilingual"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["generation", "question answering", "instruction tuning"], "datasets": ["MBZUAI/Bactrian-X"], "pipeline_tag": "text-generation"} | MaLA-LM/lucky52-bloom-7b1-no-49 | null | [
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|
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
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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": []} | cm4ker/gemma-Code-Instruct-Finetune-test | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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": []} | selvamathan-rampedup/RampedUp-Mistral-7B-v0.6 | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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"]} | ancebuc/tweet-eval-learners | null | [
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text-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | {"language": ["multilingual"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["generation", "question answering", "instruction tuning"], "datasets": ["MBZUAI/Bactrian-X"], "pipeline_tag": "text-generation"} | MaLA-LM/lucky52-bloom-7b1-no-50 | null | [
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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. -->
# gpt-neo-125m-finetuned-philosopher_rave
This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.co/E... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/gpt-neo-125m", "model-index": [{"name": "gpt-neo-125m-finetuned-philosopher_rave", "results": []}]} | ColleenMacklin/gpt-neo-125m-finetuned-philosopher_rave | null | [
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| gpt-neo-125m-finetuned-philosopher\_rave
========================================
This model is a fine-tuned version of EleutherAI/gpt-neo-125m on the Triangles/philosopher dataset.
It achieves the following results on the evaluation set:
* Loss: 2.9098
Model description
-----------------
Trained for 10 epochs
... | [
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/instructkr/lynn-7b-alpha
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/lynn-7b-alpha-i1-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of ... | {"language": ["en"], "license": "cc-by-sa-4.0", "library_name": "transformers", "tags": ["not-for-all-audiences"], "base_model": "instructkr/lynn-7b-alpha", "quantized_by": "mradermacher"} | mradermacher/lynn-7b-alpha-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
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(sorted by size, not necessarily quality. ... | [] | [
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automatic-speech-recognition | transformers |
This is a quantized form of https://huggingface.co/distil-whisper/distil-large-v3 for rwhisper | {"license": "mit"} | Demonthos/candle-quantized-whisper-distil-v3 | null | [
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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 [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) o... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "google-t5/t5-small", "model-index": [{"name": "my_awesome_billsum_model", "results": []}]} | mrigankabora9/my_awesome_billsum_model | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-04T15:03:39+00:00 | [] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #base_model-google-t5/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 google-t5/t5-small on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3652
* Rouge1: 0.182
* Rouge2: 0.0846
* Rougel: 0.1534
* Rougelsum: 0.1532
* Gen Len: 19.0
Model description
----... | [
"### 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: 4",
"### Training... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\... | [
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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. -->
# xlm-roberta-base-language-detection-finetuned
This model is a fine-tuned version of [papluca/xlm-roberta-base-language-detection... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "papluca/xlm-roberta-base-language-detection", "model-index": [{"name": "xlm-roberta-base-language-detection-finetuned", "results": []}]} | RonTon05/xlm-roberta-base-language-detection-finetuned | null | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:papluca/xlm-roberta-base-language-detection",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-04T15:05:17+00:00 | [] | [] | TAGS
#transformers #safetensors #xlm-roberta #text-classification #generated_from_trainer #base_model-papluca/xlm-roberta-base-language-detection #license-mit #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-language-detection-finetuned
=============================================
This model is a fine-tuned version of papluca/xlm-roberta-base-language-detection on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1662
* Accuracy: 0.9619
* F1: 0.9619
Model descrip... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Train... | [
"TAGS\n#transformers #safetensors #xlm-roberta #text-classification #generated_from_trainer #base_model-papluca/xlm-roberta-base-language-detection #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n... | [
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text-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | {"language": ["multilingual"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["generation", "question answering", "instruction tuning"], "datasets": ["MBZUAI/Bactrian-X"], "pipeline_tag": "text-generation"} | MaLA-LM/lucky52-bloom-7b1-no-51 | null | [
"transformers",
"pytorch",
"bloom",
"text-generation",
"generation",
"question answering",
"instruction tuning",
"multilingual",
"dataset:MBZUAI/Bactrian-X",
"arxiv:2404.04850",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:u... | null | 2024-04-04T15:07:18+00:00 | [
"2404.04850"
] | [
"multilingual"
] | TAGS
#transformers #pytorch #bloom #text-generation #generation #question answering #instruction tuning #multilingual #dataset-MBZUAI/Bactrian-X #arxiv-2404.04850 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | [
"### Model Description\n\nThis HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages. \nWe progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in... | [
"TAGS\n#transformers #pytorch #bloom #text-generation #generation #question answering #instruction tuning #multilingual #dataset-MBZUAI/Bactrian-X #arxiv-2404.04850 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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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": []} | ColleenMacklin/gpt-neo-125m-finetuned-philosopher-10e | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-04T15:08:47+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #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:
- Language(s) (NLP):
- License... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="adekhovich/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional ... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | adekhovich/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-04T15:12:42+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
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] |
text-generation | transformers |
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | {"language": ["multilingual"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["generation", "question answering", "instruction tuning"], "datasets": ["MBZUAI/Bactrian-X"], "pipeline_tag": "text-generation"} | MaLA-LM/lucky52-bloom-7b1-no-52 | null | [
"transformers",
"pytorch",
"bloom",
"text-generation",
"generation",
"question answering",
"instruction tuning",
"multilingual",
"dataset:MBZUAI/Bactrian-X",
"arxiv:2404.04850",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:u... | null | 2024-04-04T15:12:44+00:00 | [
"2404.04850"
] | [
"multilingual"
] | TAGS
#transformers #pytorch #bloom #text-generation #generation #question answering #instruction tuning #multilingual #dataset-MBZUAI/Bactrian-X #arxiv-2404.04850 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
### Model Description
This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three ... | [
"### Model Description\n\nThis HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages. \nWe progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in... | [
"TAGS\n#transformers #pytorch #bloom #text-generation #generation #question answering #instruction tuning #multilingual #dataset-MBZUAI/Bactrian-X #arxiv-2404.04850 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Model Description\n\nThis HF repos... | [
82,
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16
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"TAGS\n#transformers #pytorch #bloom #text-generation #generation #question answering #instruction tuning #multilingual #dataset-MBZUAI/Bactrian-X #arxiv-2404.04850 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Model Description\n\nThis HF repository ... |
text-generation | transformers |
Trying out some LISA training.
A few too many numbers changed to be quite directly comparable, but here's the nous-eval comparisons with the CosmoAlpacaLight using LORA:
| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
|-----------------------------... | {"license": "cc", "tags": ["generated_from_trainer"], "base_model": "HuggingFaceTB/cosmo-1b", "model-index": [{"name": "lisa-out", "results": []}]} | Lambent/CosmoAlpacaLisa-1b | null | [
"transformers",
"pytorch",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:HuggingFaceTB/cosmo-1b",
"license:cc",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-04T15:13:58+00:00 | [] | [] | TAGS
#transformers #pytorch #llama #text-generation #generated_from_trainer #base_model-HuggingFaceTB/cosmo-1b #license-cc #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Trying out some LISA training.
A few too many numbers changed to be quite directly comparable, but here's the nous-eval comparisons with the CosmoAlpacaLight using LORA:
<img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
lisa-out
========
This mod... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e... | [
"TAGS\n#transformers #pytorch #llama #text-generation #generated_from_trainer #base_model-HuggingFaceTB/cosmo-1b #license-cc #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* lea... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="adekhovich/Unit2", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Unit2", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- 2.... | adekhovich/Unit2 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-04T15:15:26+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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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": []} | Abdoulahi07/mistral_7b_yann | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-04T15:17:19+00:00 | [
"1910.09700"
] | [] | TAGS
#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:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s)... | [
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/sygenai/Yarn-Mistral-7b-SFT-Capybara-Openhermes-128k-QLoRA
<!-- provided-files -->
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 ... | {"language": ["en"], "library_name": "transformers", "base_model": "sygenai/Yarn-Mistral-7b-SFT-Capybara-Openhermes-128k-QLoRA", "quantized_by": "mradermacher"} | mradermacher/Yarn-Mistral-7b-SFT-Capybara-Openhermes-128k-QLoRA-GGUF | null | [
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"base_model:sygenai/Yarn-Mistral-7b-SFT-Capybara-Openhermes-128k-QLoRA",
"endpoints_compatible",
"region:us"
] | null | 2024-04-04T15:18:44+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-sygenai/Yarn-Mistral-7b-SFT-Capybara-Openhermes-128k-QLoRA #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 |
# Lojitha/sl_marraige-law-mistral-7b-ins-SFT
<!-- 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 aut... | {"language": ["en"], "license": "openrail", "library_name": "transformers", "tags": ["legal"], "datasets": ["Lojitha/sl_marraige_law_QA"], "pipeline_tag": "text-generation"} | Lojitha/sl_marraige-law-mistral-7b-ins-SFT | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"legal",
"conversational",
"en",
"dataset:Lojitha/sl_marraige_law_QA",
"arxiv:1910.09700",
"license:openrail",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-04T15:21:59+00:00 | [
"1910.09700"
] | [
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #legal #conversational #en #dataset-Lojitha/sl_marraige_law_QA #arxiv-1910.09700 #license-openrail #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Lojitha/sl_marraige-law-mistral-7b-ins-SFT
## 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: [Lojitha Pathirage]
- Language(s) (NLP): [English]
- License: [OpenRAIL]
- Fin... | [
"# Lojitha/sl_marraige-law-mistral-7b-ins-SFT",
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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": []} | WillHeld/via-7b-2 | null | [
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#transformers #safetensors #llama #arxiv-1910.09700 #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. -->
# zephyr-7b-ipo-qlora-v0
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/ali... | {"license": "apache-2.0", "library_name": "peft", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "zephyr-7b-ipo-qlora-v0", "results": []}]} | DUAL-GPO/zephyr-7b-ipo-qlora-v0 | null | [
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"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
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#peft #tensorboard #safetensors #mistral #alignment-handbook #generated_from_trainer #trl #dpo #dataset-HuggingFaceH4/ultrafeedback_binarized #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us
| zephyr-7b-ipo-qlora-v0
======================
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback\_binarized dataset.
It achieves the following results on the evaluation set:
* Loss: 1755.6567
* Rewards/chosen: -0.1146
* Rewards/rejected: -0.2709
* Rewards... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-06\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 4\n* optimizer: Adam with... | [
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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. -->
# zephyr-7b-gpo-update3-i0
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/a... | {"license": "apache-2.0", "library_name": "peft", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "zephyr-7b-gpo-update3-i0", "results": []}]} | DUAL-GPO/zephyr-7b-gpo-update3-i0 | null | [
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"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
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| zephyr-7b-gpo-update3-i0
========================
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback\_binarized dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0224
* Rewards/chosen: -0.1801
* Rewards/rejected: -0.2679
* Reward... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-06\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 4\n* optimizer: Adam with... | [
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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. -->
# zephyr-7b-gpo-update4-i0
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/a... | {"license": "apache-2.0", "library_name": "peft", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "zephyr-7b-gpo-update4-i0", "results": []}]} | DUAL-GPO/zephyr-7b-gpo-update4-i0 | null | [
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"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | null | 2024-04-04T15:27:57+00:00 | [] | [] | TAGS
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| zephyr-7b-gpo-update4-i0
========================
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback\_binarized dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0239
* Rewards/chosen: -0.0415
* Rewards/rejected: -0.1266
* Reward... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-06\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 4\n* optimizer: Adam with... | [
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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. -->
# zephyr-7b-dpo-qlora-v1
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/ali... | {"license": "apache-2.0", "library_name": "peft", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "zephyr-7b-dpo-qlora-v1", "results": []}]} | DUAL-GPO/zephyr-7b-dpo-qlora-v1 | null | [
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"dataset:HuggingFaceH4/ultrafeedback_binarized",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | null | 2024-04-04T15:29:34+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #mistral #alignment-handbook #generated_from_trainer #trl #dpo #dataset-HuggingFaceH4/ultrafeedback_binarized #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us
| zephyr-7b-dpo-qlora-v1
======================
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback\_binarized dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4853
* Rewards/chosen: -1.9997
* Rewards/rejected: -3.0850
* Rewards/ac... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-06\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 4\n* optimizer: Adam with... | [
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text-generation | transformers |
<p align="center">
<img src="https://huggingface.co/speakleash/Bielik-7B-Instruct-v0.1/raw/main/speakleash_cyfronet.png">
</p>
# Bielik-7B-Instruct-v0.1-3bit-HQQ
This repo contains HQQ (3-bit) format model files for [SpeakLeash](https://speakleash.org/)'s [Bielik-7B-Instruct-v0.1](https://huggingface.co/speakleash... | {"language": ["pl"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["finetuned", "hqq"], "inference": false} | speakleash/Bielik-7B-Instruct-v0.1-3bit-HQQ | null | [
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"conversational",
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"license:cc-by-nc-4.0",
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"region:us"
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|
<p align="center">
<img src="URL
</p>
# Bielik-7B-Instruct-v0.1-3bit-HQQ
This repo contains HQQ (3-bit) format model files for SpeakLeash's Bielik-7B-Instruct-v0.1.
<b><u>DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!</u></b><br>
Simple Colab notebook for te... | [
"# Bielik-7B-Instruct-v0.1-3bit-HQQ\n\nThis repo contains HQQ (3-bit) format model files for SpeakLeash's Bielik-7B-Instruct-v0.1.\n\n<b><u>DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!</u></b><br>\n\nSimple Colab notebook for testing: URL",
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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... | yann-j/dqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-04T15:31:37+00:00 | [] | [] | TAGS
#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
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/arlineka/CatNyanster-34b
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/CatNyanster-34b-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of [... | {"language": ["en"], "library_name": "transformers", "base_model": "arlineka/CatNyanster-34b", "quantized_by": "mradermacher"} | mradermacher/CatNyanster-34b-i1-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:arlineka/CatNyanster-34b",
"endpoints_compatible",
"region:us"
] | null | 2024-04-04T15:33:46+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-arlineka/CatNyanster-34b #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static 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. ... | [] | [
"TAGS\n#transformers #gguf #en #base_model-arlineka/CatNyanster-34b #endpoints_compatible #region-us \n"
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34
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text-generation | transformers |
# Jamba-Small v1
This is a pruned version of AI21 Labs' Jamba-v0.1 model that is ~25% the size of Jamba-v0.1.
## Model Details
Whereas Jamba-v0.1 contains 4 Jamba blocks, Jamba-Small contains only 1 Jamba block.
Jamba-Small's Jamba blocks follow the same structure seen in Jamba-v0.1, with a 1:7 ratio of attention-... | {"library_name": "transformers", "tags": []} | OxxoCodes/jamba-small-v1 | null | [
"transformers",
"safetensors",
"jamba",
"text-generation",
"arxiv:2403.19887",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-04T15:34:05+00:00 | [
"2403.19887"
] | [] | TAGS
#transformers #safetensors #jamba #text-generation #arxiv-2403.19887 #autotrain_compatible #endpoints_compatible #region-us
|
# Jamba-Small v1
This is a pruned version of AI21 Labs' Jamba-v0.1 model that is ~25% the size of Jamba-v0.1.
## Model Details
Whereas Jamba-v0.1 contains 4 Jamba blocks, Jamba-Small contains only 1 Jamba block.
Jamba-Small's Jamba blocks follow the same structure seen in Jamba-v0.1, with a 1:7 ratio of attention-... | [
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automatic-speech-recognition | 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. -->
# hubert-base-common-voice-vi-demo
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/faceb... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_16_1"], "metrics": ["wer"], "base_model": "facebook/hubert-base-ls960", "model-index": [{"name": "hubert-base-common-voice-vi-demo", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognitio... | ntxcong/hubert-base-common-voice-vi-demo | null | [
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| hubert-base-common-voice-vi-demo
================================
This model is a fine-tuned version of facebook/hubert-base-ls960 on the common\_voice\_16\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5121
* Wer: 0.3678
Model description
-----------------
More information neede... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\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* lr\\_scheduler\\_warmup\\_steps... | [
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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. -->
# gpt-neo-125m-finetuned-philosopher_rave_20
This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.c... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/gpt-neo-125m", "model-index": [{"name": "gpt-neo-125m-finetuned-philosopher_rave_20", "results": []}]} | ColleenMacklin/gpt-neo-125m-finetuned-philosopher_rave_20 | null | [
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| gpt-neo-125m-finetuned-philosopher\_rave\_20
============================================
This model is a fine-tuned version of EleutherAI/gpt-neo-125m on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.7097
Model description
-----------------
More information needed
Int... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-07\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: 20.0",
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/TroyDoesAI/MermaidMixtral-2x6.5b
<!-- provided-files -->
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 ... | {"language": ["en"], "license": "cc-by-4.0", "library_name": "transformers", "base_model": "TroyDoesAI/MermaidMixtral-2x6.5b", "quantized_by": "mradermacher"} | mradermacher/MermaidMixtral-2x6.5b-GGUF | null | [
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#transformers #gguf #en #base_model-TroyDoesAI/MermaidMixtral-2x6.5b #license-cc-by-4.0 #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 |
# 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": ["unsloth", "trl", "sft"]} | olvbm/alexandria-mistral | 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.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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automatic-speech-recognition | 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. -->
# Whisper Small Dv - Sanchit Gandhi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whi... | {"language": ["dv"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_13_0"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small Dv - Sanchit Gandhi", "results": [{"task": {"type": "automatic-speech-recognition", "n... | marcellopoliti/whisper-small-dv | null | [
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| Whisper Small Dv - Sanchit Gandhi
=================================
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1752
* Wer Ortho: 63.6674
* Wer: 13.5689
Model description
-----------------
More info... | [
"### 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: constant\\_with\\_warmup\n* lr\\_schedule... | [
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null | transformers | <h1 style="text-align: center">Twizzler-7B GGUF</h1>
<div style="display: flex; justify-content: center;">
<img src="https://huggingface.co/son-of-man/Twizzler-7B/resolve/main/twizz.jpg" alt="Header JPG">
</div>
I tried to expand [Erosumika](https://huggingface.co/localfultonextractor/Erosumika-7B-v3) with more... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Severian/Nexus-IKM-Mistral-Instruct-v0.2-7B", "son-of-man/HoloViolet-7B-test3", "alpindale/Mistral-7B-v0.2-hf", "localfultonextractor/Erosumika-7B-v3"]} | son-of-man/Twizzler-7B-GGUF | null | [
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| <h1 style="text-align: center">Twizzler-7B GGUF</h1>
<div style="display: flex; justify-content: center;">
<img src="URL alt="Header JPG">
</div>
I tried to expand Erosumika with more abilities while keeping her brain intact.
The first key to this was to inject a small amount of a highly volatile Holoviolet te... | [
"# Prompts and settings\n\nI recommend simple formats like Alpaca and not giving it too many instructions to get confused by. It is a 7B after all.\n\nAs for settings, I enjoy using dynamic temperature 1 to 5 with a min P of 0.1 and 0.95 typical P.",
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sentence-similarity | sentence-transformers |
# peulsilva/phrase-bert-setfit-50shots-RAFT-ETHOS
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | peulsilva/phrase-bert-setfit-50shots-RAFT-ETHOS | null | [
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#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# peulsilva/phrase-bert-setfit-50shots-RAFT-ETHOS
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transf... | [
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/distilbert-distilgpt2-bnb-4bit-smashed | null | [
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.URL alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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![Twitter](URL
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"# Simply make AI models cheaper, smaller, faster, and greener!\n\n- Give a thumbs up if you like this model!\n- Contact us and tell us which model to compress next here.\n- Request access to easily compress your *own* AI models here.\n- Read the documentations to know more here\n- Join Pruna AI community on Discor... | [
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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": []} | sidmanale643/gemma-2B-marathi-translation | null | [
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"1910.09700"
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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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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/son-of-man/Twizzler-7B
<!-- provided-files -->
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. ... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "son-of-man/Twizzler-7B", "quantized_by": "mradermacher"} | mradermacher/Twizzler-7B-GGUF | null | [
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| 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 | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/distilbert-distilgpt2-bnb-8bit-smashed | null | [
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![Twitter](URL
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text-generation | transformers |
EXL2 quants of [bcse/Bernstein-120b](https://huggingface.co/bcse/Bernstein-120b)
---
base_model:
- ShinojiResearch/Senku-70B-Full
- Sao10K/Euryale-1.3-L2-70B
library_name: transformers
tags:
- mergekit
- merge
---
# Bernstein-120b
This is a merge of pre-trained language models created using [mergekit](https://githu... | {} | SatouLilly/Bernstein-120b-3.0bpw-h6-exl2 | null | [
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"2203.05482"
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|
EXL2 quants of bcse/Bernstein-120b
---
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- ShinojiResearch/Senku-70B-Full
- Sao10K/Euryale-1.3-L2-70B
library_name: transformers
tags:
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- merge
---
# Bernstein-120b
This is a merge of pre-trained language models created using mergekit.
## Quants
* mradermacher/Bernstein-120b-GGUF
* mradermache... | [
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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. -->
# tweet-eval-sentiment
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an u... | {"license": "apache-2.0", "tags": ["classification", "generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "tweet-eval-sentiment", "results": []}]} | ancebuc/tweet-eval-sentiment | null | [
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| tweet-eval-sentiment
====================
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: 1.0651
* Accuracy: 0.4759
Model description
-----------------
More information needed
Intended uses & limitations
----------... | [
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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": []} | salangarica/BioMistral-RAG-k1 | 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]:
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text2text-generation | 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. -->
# ulasbilgen/my_awesome_billsum_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown da... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "t5-small", "model-index": [{"name": "ulasbilgen/my_awesome_billsum_model", "results": []}]} | ulasbilgen/my_awesome_billsum_model | null | [
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| ulasbilgen/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:
* Train Loss: 3.6408
* Validation Loss: 2.9496
* Epoch: 0
Model description
-----------------
More informat... | [
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/openai-community-gpt2-bnb-4bit-smashed | null | [
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<a href="URL target="_blank" rel="noopener noreferrer">
<img src="https://i.URL alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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![Twitter](URL
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"# Simply make AI models cheaper, smaller, faster, and greener!\n\n- Give a thumbs up if you like this model!\n- Contact us and tell us which model to compress next here.\n- Request access to easily compress your *own* AI models here.\n- Read the documentations to know more here\n- Join Pruna AI community on Discor... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="adekhovich/Unit2_v2", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Unit2_v2", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.54 +/-... | adekhovich/Unit2_v2 | null | [
"Taxi-v3",
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#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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] |
question-answering | 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. -->
# jarvis-qa-model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "jarvis-qa-model", "results": []}]} | siddhuggingface/jarvis-qa-model | null | [
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#transformers #safetensors #distilbert #question-answering #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #endpoints_compatible #region-us
| jarvis-qa-model
===============
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: 1.7669
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
Mor... | [
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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": "BramVanroy/GEITje-7B-ultra"} | HansvDam/GEITje-7B-ultra-sr-system2-do-adapters | null | [
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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": []} | salangarica/BioMistral-RAG-k0 | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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": []} | HansvDam/GEITje-7B-ultra-sr-system2-do | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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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. -->
# gpt-neo-125m-finetuned-philosopher_rave_100
This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/gpt-neo-125m", "model-index": [{"name": "gpt-neo-125m-finetuned-philosopher_rave_100", "results": []}]} | ColleenMacklin/gpt-neo-125m-finetuned-philosopher_rave_100 | null | [
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| gpt-neo-125m-finetuned-philosopher\_rave\_100
=============================================
This model is a fine-tuned version of EleutherAI/gpt-neo-125m on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3681
Model description
-----------------
More information needed
I... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-07\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: 100.0",
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="adekhovich/Unit2_v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Unit2_v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.54 +/-... | adekhovich/Unit2_v3 | null | [
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#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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fill-mask | 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-imdb
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-imdb", "results": []}]} | walterg777/distilbert-base-uncased-finetuned-imdb | null | [
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| distilbert-base-uncased-finetuned-imdb
======================================
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: 2.4894
Model description
-----------------
More information needed
Intended uses &... | [
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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": []} | salangarica/BioMistral-RAG-k2 | null | [
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fill-mask | 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": []} | Sotaro0124/as_xlm | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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": []} | kgoedert/whisper-large-v3-pt-mzcv16-model | null | [
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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. -->
# en_vi_envit5-translation_conv_train
This model is a fine-tuned version of [VietAI/envit5-translation](https://huggingface.co/Vie... | {"license": "openrail", "tags": ["generated_from_trainer"], "base_model": "VietAI/envit5-translation", "model-index": [{"name": "en_vi_envit5-translation_conv_train", "results": []}]} | yuufong/en_vi_envit5-translation_conv_train | null | [
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|
# en_vi_envit5-translation_conv_train
This model is a fine-tuned version of VietAI/envit5-translation on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### T... | [
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fill-mask | 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": []} | Sotaro0124/as_xlm_5 | null | [
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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. -->
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"TAGS\n#transformers #pytorch #gemma #text-generation #unsloth #trl #sft #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that ha... |
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... | DucciGang/LunarModel | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-04T16:00:26+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-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... | {"license": "mit", "library_name": "transformers"} | Shaleen123/phi-2-maths | null | [
"transformers",
"safetensors",
"phi",
"text-generation",
"custom_code",
"arxiv:1910.09700",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-04T16:02:38+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #phi #text-generation #custom_code #arxiv-1910.09700 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #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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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **ALE/Pacman-v5**
This is a trained model of a **DQN** agent playing **ALE/Pacman-v5**
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 framework for Stable Baselines3
rein... | {"library_name": "stable-baselines3", "tags": ["ALE/Pacman-v5", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ALE/Pacman-v5", "type": "ALE/Pacm... | ledmands/dqn-Pacman-v5_colabtest | null | [
"stable-baselines3",
"ALE/Pacman-v5",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-04T16:03:23+00:00 | [] | [] | TAGS
#stable-baselines3 #ALE/Pacman-v5 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing ALE/Pacman-v5
This is a trained model of a DQN agent playing ALE/Pacman-v5
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with S... | [
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"#... | [
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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. -->
Trying out some LISA training.
This one used the same learning rate as the LORA training and only 4 layers each 10 steps.
Honestly ... | {"license": "cc", "tags": ["generated_from_trainer"], "base_model": "HuggingFaceTB/cosmo-1b", "model-index": [{"name": "lisa-out", "results": []}]} | Lambent/CosmoAlpacaLisa-0.2-1b | null | [
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"pytorch",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:HuggingFaceTB/cosmo-1b",
"license:cc",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-04T16:05:08+00:00 | [] | [] | TAGS
#transformers #pytorch #llama #text-generation #generated_from_trainer #base_model-HuggingFaceTB/cosmo-1b #license-cc #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Trying out some LISA training.
This one used the same learning rate as the LORA training and only 4 layers each 10 steps.
Honestly these numbers are probably noise, with how close they are.
<img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
lisa-ou... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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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": []} | Ftest/CustomLlava | null | [
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"safetensors",
"llava_llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #llava_llama #text-generation #arxiv-1910.09700 #autotrain_compatible #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:
- Language(s) (NLP):
- License... | [
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text-classification | 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. -->
# reward-opi-reddit-epochs-30
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-mult... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "bert-base-multilingual-cased", "model-index": [{"name": "reward-opi-reddit-epochs-30", "results": []}]} | tatai08/reward-opi-reddit-epochs-30 | null | [
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"bert",
"text-classification",
"generated_from_keras_callback",
"base_model:bert-base-multilingual-cased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-04T16:05:59+00:00 | [] | [] | TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #base_model-bert-base-multilingual-cased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| reward-opi-reddit-epochs-30
===========================
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.1744
* Train Accuracy: 0.9468
* Validation Loss: 2.5324
* Validation Accuracy: 0.8363
* Epoch: 28... | [
"### 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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text-to-image | diffusers | ### My-Pet-Dog Dreambooth model trained by shabnamn following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX19932gAS
Sample pictures of this concept:
.jpg)
![1](https://huggingfac... | {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | shabnamn/my-pet-dog | null | [
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"region:us"
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#diffusers #safetensors #NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
| ### My-Pet-Dog Dreambooth model trained by shabnamn following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX19932gAS
Sample pictures of this concept:
!0.jpg)
!1.jpg)
!2.jpg)
!3.jpg)
!4.jpg)
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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. -->
# Mistral_for_us
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistr... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "Mistral_for_us", "results": []}]} | vierpiet/Mistral_for_us | null | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-04T16:08:05+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
|
# Mistral_for_us
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperp... | [
"# Mistral_for_us\n\nThis model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset.",
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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
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text-generation | transformers |
EXL2 quants of [bcse/Lumiere-120b](https://huggingface.co/bcse/Lumiere-120b)
---
base_model:
- Undi95/Miqu-70B-Alpaca-DPO
- Sao10K/Euryale-1.3-L2-70B
library_name: transformers
tags:
- mergekit
- merge
---
# Lumiere-120b
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg12... | {} | SatouLilly/Lumiere-120b-3.0bpw-h6-exl2 | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2203.05482",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"3-bit",
"region:us"
] | null | 2024-04-04T16:08:49+00:00 | [
"2203.05482"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #arxiv-2203.05482 #autotrain_compatible #endpoints_compatible #text-generation-inference #3-bit #region-us
|
EXL2 quants of bcse/Lumiere-120b
---
base_model:
- Undi95/Miqu-70B-Alpaca-DPO
- Sao10K/Euryale-1.3-L2-70B
library_name: transformers
tags:
- mergekit
- merge
---
# Lumiere-120b
This is a merge of pre-trained language models created using mergekit.
## Quants
* mradermacher/Lumiere-120b-GGUF
* mradermacher/Lumiere-... | [
"# Lumiere-120b\n\nThis is a merge of pre-trained language models created using mergekit.",
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"## Merge Details",
"### Merge Method\n\nThis model was merged using the linear merge method.",
"### Models Merged\n\nThe followin... | [
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null | null |
### Model Description
This HF repository contains base LLMs instruction tuned (SFT) with full-parameter fine-tuning and then used to study whether monolingual or multilingual instruction tuning is more favourable.
* [GitHub](https://github.com/hplt-project/monolingual-multilingual-instruction-tuning/tree/main)
* [Pa... | {"language": ["pt"], "license": "cc-by-nc-4.0", "tags": ["generation", "question answering", "instruction tuning"]} | HPLT/sft-fpft-pt-bloom-560m | null | [
"generation",
"question answering",
"instruction tuning",
"pt",
"arxiv:2309.08958",
"license:cc-by-nc-4.0",
"region:us"
] | null | 2024-04-04T16:09:09+00:00 | [
"2309.08958"
] | [
"pt"
] | TAGS
#generation #question answering #instruction tuning #pt #arxiv-2309.08958 #license-cc-by-nc-4.0 #region-us
|
### Model Description
This HF repository contains base LLMs instruction tuned (SFT) with full-parameter fine-tuning and then used to study whether monolingual or multilingual instruction tuning is more favourable.
* GitHub
* Paper
#### Instruction tuning details
* Base model: bloom-560m
* Instruction tuning languag... | [
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text-classification | transformers |
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 0.001261080033145845
f1: 1.0
precision: 1.0
recall: 1.0
auc: 1.0
accuracy: 1.0
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# Model Trained Using AutoTrain
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## Validation Metrics
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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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. -->
# roberta-base_ai4privacy_en
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/rob... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "roberta-base_ai4privacy_en", "results": []}]} | xXiaobuding/roberta-base_ai4privacy_en | null | [
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| roberta-base\_ai4privacy\_en
============================
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0962
* Overall Precision: 0.8739
* Overall Recall: 0.9046
* Overall F1: 0.8890
* Overall Accuracy: 0.9623
... | [
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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": []} | Manan28/Finllama2-finetuned | null | [
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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. -->
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text2text-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": []} | tareknaous/mt5-base-readme-en | null | [
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text-generation | transformers |
### Model Description
This HF repository contains base LLMs instruction tuned (SFT) with full-parameter fine-tuning and then used to study whether monolingual or multilingual instruction tuning is more favourable.
* [GitHub](https://github.com/hplt-project/monolingual-multilingual-instruction-tuning/tree/main)
* [Pa... | {"language": ["bg"], "license": "cc-by-nc-4.0", "tags": ["generation", "question answering", "instruction tuning"]} | HPLT/sft-fpft-bg-bloom-560m | null | [
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|
### Model Description
This HF repository contains base LLMs instruction tuned (SFT) with full-parameter fine-tuning and then used to study whether monolingual or multilingual instruction tuning is more favourable.
* GitHub
* Paper
#### Instruction tuning details
* Base model: bloom-560m
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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. -->
# robust_llm_pythia-tt-14m-mz-advt-v0-ts-20000-s-2
This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingfa... | {"tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-14m", "model-index": [{"name": "robust_llm_pythia-tt-14m-mz-advt-v0-ts-20000-s-2", "results": []}]} | AlignmentResearch/robust_llm_pythia-tt-14m-mz-advt-v0-ts-20000-s-2 | null | [
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|
# robust_llm_pythia-tt-14m-mz-advt-v0-ts-20000-s-2
This model is a fine-tuned version of EleutherAI/pythia-14m on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedu... | [
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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. -->
# robust_llm_pythia-tt-31m-mz-advt-v0-ts-2000-s-2
This model is a fine-tuned version of [EleutherAI/pythia-31m](https://huggingfac... | {"tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-31m", "model-index": [{"name": "robust_llm_pythia-tt-31m-mz-advt-v0-ts-2000-s-2", "results": []}]} | AlignmentResearch/robust_llm_pythia-tt-31m-mz-advt-v0-ts-2000-s-2 | null | [
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"text-generation-inference",
"region:us"
] | null | 2024-04-04T16:12:41+00:00 | [] | [] | TAGS
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|
# robust_llm_pythia-tt-31m-mz-advt-v0-ts-2000-s-2
This model is a fine-tuned version of EleutherAI/pythia-31m on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedur... | [
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