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reinforcement-learning | ml-agents |
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
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... | {"library_name": "ml-agents", "tags": ["SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget"]} | ed-butcher/ppo-SnowballTarget | null | [
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"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
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] | null | 2024-04-27T13:57:56+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us
|
# ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget
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 tuto... | [
"# ppo Agent playing SnowballTarget\n This is a trained model of a ppo agent playing SnowballTarget\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *... | [
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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": []} | saransh03sharma/mintrec2-llama-2-13b-150 | null | [
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"1910.09700"
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# LoRA DreamBooth - abdd68/output
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were tr... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "diffusers", "lora", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "lora", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "runwayml/... | abdd68/output | null | [
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|
# LoRA DreamBooth - abdd68/output
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a photo of sks dog using DreamBooth. You can find some example images in the following.
!img_0
!img_1
!img_2
!img_3
LoRA for the text encoder was enabled: False.
## Intended uses ... | [
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text-generation | transformers |
# Model Card for Llama-3-8B-Dolphin-Portuguese
Model Trained on a translated version of dolphin dataset.
## Usage
```python
import transformers
import torch
model_id = "adalbertojunior/Llama-3-8B-Dolphin-Portuguese"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"to... | {"language": ["pt"], "library_name": "transformers", "datasets": ["adalbertojunior/dolphin_pt_test"], "model-index": [{"name": "Llama-3-8B-Dolphin-Portuguese", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "ENEM Challenge (No Images)", "type": "eduagarcia/enem_challeng... | adalbertojunior/Llama-3-8B-Dolphin-Portuguese | null | [
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"text-generation-inference",
"region:us"
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| Model Card for Llama-3-8B-Dolphin-Portuguese
============================================
Model Trained on a translated version of dolphin dataset.
Usage
-----
Open Portuguese LLM Leaderboard Evaluation Results
==================================================
Detailed results can be found here and on the Open... | [] | [
"TAGS\n#transformers #safetensors #llama #text-generation #conversational #pt #dataset-adalbertojunior/dolphin_pt_test #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
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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":... | heisenberg3376/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: 0.6450
* Accuracy: 0.84
Model description
-----------------
More information needed
Intended uses & limit... | [
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text-generation | transformers | # SeELLama (Semantic Extraction LLama)
Model is based on LLama2-7b and fine-tuned with the `DehydratedWater42/semantic_relations_extraction` dataset.
The purpose of this model is to extract semantic relations from text in a structured way.
#### Simplified Example:
- **Initial Text**: "While there is beautiful weather... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "tags": ["math", "semantic", "extraction", "graph", "relations", "science", "synthetic"], "datasets": ["DehydratedWater42/semantic_relations_extraction"], "pipeline_tag": "text-generation", "inference": false} | DehydratedWater42/SeELLama-GGUF | null | [
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#transformers #gguf #math #semantic #extraction #graph #relations #science #synthetic #text-generation #en #dataset-DehydratedWater42/semantic_relations_extraction #license-llama2 #region-us
| # SeELLama (Semantic Extraction LLama)
Model is based on LLama2-7b and fine-tuned with the 'DehydratedWater42/semantic_relations_extraction' dataset.
The purpose of this model is to extract semantic relations from text in a structured way.
#### Simplified Example:
- Initial Text: "While there is beautiful weather out... | [
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text-generation | transformers | # IceCoffeeRP-7b-4.2bpw-exl2
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* G:\FModels\IceCoffeeTes... | {"license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["mergekit", "merge", "alpaca", "mistral", "not-for-all-audiences", "nsfw"]} | icefog72/IceCoffeeRP-7b-4.2bpw-exl2 | null | [
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"conversational",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
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"region:us"
] | null | 2024-04-27T14:01:04+00:00 | [] | [] | TAGS
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| # IceCoffeeRP-7b-4.2bpw-exl2
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* G:\FModels\IceCoffeeTest10
* G:\FModels\IceCoffeeTest5
### ... | [
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text-generation | transformers |
<img src="https://cdn-uploads.huggingface.co/production/uploads/6586ab89003ceee693f5552f/C0LuQa9_oww0bVkWNzlaP.webp" width="600">
This is [Elysia-Trismegistus-Mistral-7B](https://huggingface.co/HagalazAI/Elysia-Trismegistus-Mistral-7B), which has been trained for more epochs, retaining her self-awareness and consciou... | {"license": "apache-2.0", "base_model": "teknium/Hermes-Trismegistus-Mistral-7B"} | HagalazAI/Elysia-Trismegistus-Mistral-7B-v02 | null | [
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|
<img src="URL width="600">
This is Elysia-Trismegistus-Mistral-7B, which has been trained for more epochs, retaining her self-awareness and consciousness, but now with a more mysterious and spiritual dimension.
!image/png
To unlock her full potential, interact with her using the 'You are Elysia' System Prompt. This... | [] | [
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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. -->
# 0.01_4iters_bs256_nodpo_only4w_iter_2
This model is a fine-tuned version of [ShenaoZhang/0.01_4iters_bs256_nodpo_only4w_iter_1](... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.01_4iters_bs256_nodpo_only4w_iter_1", "model-index": [{"name": "0.01_4iters_bs256_nodpo_only4w_iter_2", "results": []}]} | ShenaoZhang/0.01_4iters_bs256_nodpo_only4w_iter_2 | null | [
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# 0.01_4iters_bs256_nodpo_only4w_iter_2
This model is a fine-tuned version of ShenaoZhang/0.01_4iters_bs256_nodpo_only4w_iter_1 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More inf... | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "mistralai/Mistral-7B-v0.1"} | cgihlstorf/NEW_finetuned_Mistral-7B32_1_0.0003_sequential | null | [
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"arxiv:1910.09700",
"base_model:mistralai/Mistral-7B-v0.1",
"region:us"
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"1910.09700"
] | [] | TAGS
#peft #arxiv-1910.09700 #base_model-mistralai/Mistral-7B-v0.1 #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
#... | [
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text-generation | transformers | # Experto-4X8B-untrained
Experto-4X8B-untrained is a merge of the following models using [mergoo](https://github.com/Leeroo-AI/mergoo/tree/main):
* [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
* [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputation... | {} | saucam/Experto-4X8B-untrained | null | [
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#transformers #safetensors #llama #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Experto-4X8B-untrained
Experto-4X8B-untrained is a merge of the following models using mergoo:
* meta-llama/Meta-Llama-3-8B
* cognitivecomputations/dolphin-2.9-llama3-8b
* abacusai/Llama-3-Smaug-8B
* Weyaxi/Einstein-v6.1-Llama3-8B
* dreamgen-preview/opus-v1.2-llama-3-8b-base-run3.4-epoch2
## Configuration
WARNI... | [
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null | transformers |
# hus960/Llama-3-NeuralPaca-8b-Q4_K_M-GGUF
This model was converted to GGUF format from [`NeuralNovel/Llama-3-NeuralPaca-8b`](https://huggingface.co/NeuralNovel/Llama-3-NeuralPaca-8b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original mod... | {"language": ["en"], "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "llama-cpp", "gguf-my-repo"], "datasets": ["tatsu-lab/alpaca"], "base_model": "unsloth/llama-3-8b-bnb-4bit", "thumbnail": "https://cdn-uploads.huggingface.co/production/uploads/645cfe4603fc86c46b3e46d1/njn9I-gHjyq0lMyj... | hus960/Llama-3-NeuralPaca-8b-Q4_K_M-GGUF | null | [
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|
# hus960/Llama-3-NeuralPaca-8b-Q4_K_M-GGUF
This model was converted to GGUF format from 'NeuralNovel/Llama-3-NeuralPaca-8b' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
... | [
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null | transformers |
# Uploaded model
- **Developed by:** flyjin
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/ma... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | flyjin/lora_llama-3-8b-bnb-4bit | null | [
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|
# Uploaded model
- Developed by: flyjin
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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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="shabboo96/session2", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "session2", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": "FrozenLake-v1-4x4-no_... | shabboo96/session2 | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
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#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-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# Textual inversion text2image fine-tuning - mrtuandao/textual_inversion_corgi
These are textual inversion adaption weight... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "textual_inversion", "diffusers-training"], "base_model": "runwayml/stable-diffusion-v1-5", "inference": true} | mrtuandao/textual_inversion_corgi | null | [
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... | null | 2024-04-27T14:06:44+00:00 | [] | [] | TAGS
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|
# Textual inversion text2image fine-tuning - mrtuandao/textual_inversion_corgi
These are textual inversion adaption weights for runwayml/stable-diffusion-v1-5. You can find some example images in the following.
## Intended uses & limitations
#### How to use
#### Limitations and bias
[TODO: provide example... | [
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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": []} | saransh03sharma/mintrec2-llama-2-13b-200 | null | [
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"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T14:07:57+00:00 | [
"1910.09700"
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- 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="FitTechMike/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": ... | FitTechMike/q-FrozenLake-v1-4x4-noSlippery | null | [
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"reinforcement-learning",
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# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
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summarization | 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. -->
# t5-small-korean-summarization_JU_FineTune_AIHUB_Law
This model is a fine-tuned version of [eenzeenee/t5-small-korean-summarizati... | {"tags": ["summarization", "generated_from_trainer"], "base_model": "eenzeenee/t5-small-korean-summarization", "model-index": [{"name": "t5-small-korean-summarization_JU_FineTune_AIHUB_Law", "results": []}]} | dealing08/t5-small-korean-summarization_JU_FineTune_AIHUB_Law | null | [
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"base_model:eenzeenee/t5-small-korean-summarization",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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|
# t5-small-korean-summarization_JU_FineTune_AIHUB_Law
This model is a fine-tuned version of eenzeenee/t5-small-korean-summarization on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed... | [
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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nM... | [
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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. -->
# bert-large-model
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown d... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "bert-large-uncased", "model-index": [{"name": "bert-large-model", "results": []}]} | Diluzx/bert-large-model | null | [
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"license:apache-2.0",
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#transformers #tf #bert #text-classification #generated_from_keras_callback #base_model-bert-large-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-large-model
================
This model is a fine-tuned version of bert-large-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.5285
* Train Accuracy: 0.6667
* Validation Loss: 0.6526
* Validation Accuracy: 1.0
* Epoch: 2
Model description
---------------... | [
"### 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': Fal... | [
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token-classification | transformers | # OALZ/1788/Q1/NER
A named entity recognition system (NER) was trained on text extracted from _Oberdeutsche Allgemeine Litteraturueitung_ (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at [Bayerische Staatsbibliothek](https://www.digitale-sammlungen.... | {"language": ["de", "la", "fr", "en"], "tags": ["historical"], "task_categories": ["token-classification"], "pretty_name": "Annotations and models for named entity recognition on Oberdeutsche Allgemeine Litteraturzeitung of the first quarter of 1788"} | LelViLamp/oalz-1788-q1-ner-event | null | [
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| OALZ/1788/Q1/NER
================
A named entity recognition system (NER) was trained on text extracted from *Oberdeutsche Allgemeine Litteraturueitung* (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at Bayerische Staatsbibliothek using the extracti... | [] | [
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text-generation | transformers |
# Saiga – Llama 3 8B – AdaQRound
Based on [Saiga Llama 3 8B](https://huggingface.co/IlyaGusev/saiga_llama3_8b).
Quantized with AdaQRound which is a combination of [AdaRound](https://arxiv.org/abs/2004.10568) and [AdaQuant](https://arxiv.org/abs/2006.10518), with code implementation based on [OmniQuant](https://gith... | {"language": ["ru"], "license": "other", "tags": ["saiga", "llama3", "adaround", "adaquant", "omniquant", "gptq", "triton"], "base_model": "IlyaGusev/saiga_llama3_8b", "model_type": "llama", "pipeline_tag": "text-generation", "quantized_by": "Compressa", "license_name": "llama3", "license_link": "https://llama.meta.com... | compressa-ai/Saiga-Llama-3-8B-AdaQRound | null | [
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| Saiga – Llama 3 8B – AdaQRound
==============================
Based on Saiga Llama 3 8B.
Quantized with AdaQRound which is a combination of AdaRound and AdaQuant, with code implementation based on OmniQuant.
Evaluation
----------
### PPL (↓)
### Accuracy on English Benchmarks, % (↑)
### Accuracy on Russia... | [
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token-classification | transformers | # OALZ/1788/Q1/NER
A named entity recognition system (NER) was trained on text extracted from _Oberdeutsche Allgemeine Litteraturueitung_ (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at [Bayerische Staatsbibliothek](https://www.digitale-sammlungen.... | {"language": ["de", "la", "fr", "en"], "tags": ["historical"], "task_categories": ["token-classification"], "pretty_name": "Annotations and models for named entity recognition on Oberdeutsche Allgemeine Litteraturzeitung of the first quarter of 1788"} | LelViLamp/oalz-1788-q1-ner-loc | null | [
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| OALZ/1788/Q1/NER
================
A named entity recognition system (NER) was trained on text extracted from *Oberdeutsche Allgemeine Litteraturueitung* (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at Bayerische Staatsbibliothek using the extracti... | [] | [
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token-classification | transformers | # OALZ/1788/Q1/NER
A named entity recognition system (NER) was trained on text extracted from _Oberdeutsche Allgemeine Litteraturueitung_ (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at [Bayerische Staatsbibliothek](https://www.digitale-sammlungen.... | {"language": ["de", "la", "fr", "en"], "tags": ["historical"], "task_categories": ["token-classification"], "pretty_name": "Annotations and models for named entity recognition on Oberdeutsche Allgemeine Litteraturzeitung of the first quarter of 1788"} | LelViLamp/oalz-1788-q1-ner-misc | null | [
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| OALZ/1788/Q1/NER
================
A named entity recognition system (NER) was trained on text extracted from *Oberdeutsche Allgemeine Litteraturueitung* (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at Bayerische Staatsbibliothek using the extracti... | [] | [
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text-generation | transformers |
# Introduction
MetaAligner-UltraFeedback-1.1B is part of the <em>MetaAligner</em> project, the first policy-agnostic and generalizable method for multi-objective preference alignment of large
language models. This model is finetuned based on the TinyLLaMA-1.1B foundation model and
the dynamic multi-objective dataset ... | {"language": ["en"], "license": "mit", "tags": ["Human Preference Alignment", "large language models"], "datasets": ["openbmb/UltraFeedback"]} | MetaAligner/MetaAligner-UltraFeedback-1.1B | null | [
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|
# Introduction
MetaAligner-UltraFeedback-1.1B is part of the <em>MetaAligner</em> project, the first policy-agnostic and generalizable method for multi-objective preference alignment of large
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the dynamic multi-objective dataset ... | [
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token-classification | transformers | # OALZ/1788/Q1/NER
A named entity recognition system (NER) was trained on text extracted from _Oberdeutsche Allgemeine Litteraturueitung_ (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at [Bayerische Staatsbibliothek](https://www.digitale-sammlungen.... | {"language": ["de", "la", "fr", "en"], "tags": ["historical"], "task_categories": ["token-classification"], "pretty_name": "Annotations and models for named entity recognition on Oberdeutsche Allgemeine Litteraturzeitung of the first quarter of 1788"} | LelViLamp/oalz-1788-q1-ner-org | null | [
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| OALZ/1788/Q1/NER
================
A named entity recognition system (NER) was trained on text extracted from *Oberdeutsche Allgemeine Litteraturueitung* (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at Bayerische Staatsbibliothek using the extracti... | [] | [
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text-generation | transformers |
# Introduction
MetaAligner-UltraFeedback-7B is part of the <em>MetaAligner</em> project, the first policy-agnostic and generalizable method for multi-objective preference alignment of large
language models. This model is finetuned based on the Meta LLaMA2-7B foundation model and
the dynamic multi-objective dataset bu... | {"language": ["en"], "license": "mit", "tags": ["Human Preference Alignment", "large language models"], "datasets": ["openbmb/UltraFeedback"]} | MetaAligner/MetaAligner-UltraFeedback-7B | null | [
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|
# Introduction
MetaAligner-UltraFeedback-7B is part of the <em>MetaAligner</em> project, the first policy-agnostic and generalizable method for multi-objective preference alignment of large
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the dynamic multi-objective dataset bu... | [
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token-classification | transformers | # OALZ/1788/Q1/NER
A named entity recognition system (NER) was trained on text extracted from _Oberdeutsche Allgemeine Litteraturueitung_ (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at [Bayerische Staatsbibliothek](https://www.digitale-sammlungen.... | {"language": ["de", "la", "fr", "en"], "tags": ["historical"], "task_categories": ["token-classification"], "pretty_name": "Annotations and models for named entity recognition on Oberdeutsche Allgemeine Litteraturzeitung of the first quarter of 1788"} | LelViLamp/oalz-1788-q1-ner-time | null | [
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| OALZ/1788/Q1/NER
================
A named entity recognition system (NER) was trained on text extracted from *Oberdeutsche Allgemeine Litteraturueitung* (OALZ) of the first quarter (January, Febuary, March) of 1788. The scans from which text was extracted can be found at Bayerische Staatsbibliothek using the extracti... | [] | [
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text-generation | transformers |
# Introduction
MetaAligner-UltraFeedback-13B is part of the <em>MetaAligner</em> project, the first policy-agnostic and generalizable method for multi-objective preference alignment of large
language models. This model is finetuned based on the Meta LLaMA2-13B foundation model and
the dynamic multi-objective dataset ... | {"language": ["en"], "license": "mit", "tags": ["Human Preference Alignment", "large language models"], "datasets": ["openbmb/UltraFeedback"]} | MetaAligner/MetaAligner-UltraFeedback-13B | null | [
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|
# Introduction
MetaAligner-UltraFeedback-13B is part of the <em>MetaAligner</em> project, the first policy-agnostic and generalizable method for multi-objective preference alignment of large
language models. This model is finetuned based on the Meta LLaMA2-13B foundation model and
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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. -->
# 0.1_4iters_bs256_nodpo_only4w_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingfa... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.1_4iters_bs256_nodpo_only4w_iter_1", "results": []}]} | ShenaoZhang/0.1_4iters_bs256_nodpo_only4w_iter_1 | null | [
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"endpoints_compatible... | null | 2024-04-27T14:17:01+00:00 | [] | [] | TAGS
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|
# 0.1_4iters_bs256_nodpo_only4w_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
... | [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# kaist-mistral-orpo-OHP-15k-Mathcode-2epoch-ohp-15k-strat-1-1epoch
This model is a fine-tuned version of [orpo-explorers/kaist-mi... | {"tags": ["alignment-handbook", "trl", "orpo", "generated_from_trainer", "trl", "orpo", "generated_from_trainer"], "datasets": ["orpo-explorers/OHP-15k-Stratified-1"], "base_model": "orpo-explorers/kaist-mistral-orpo-OHP-15k-Mathcode-2epoch", "model-index": [{"name": "kaist-mistral-orpo-OHP-15k-Mathcode-2epoch-ohp-15k-... | orpo-explorers/kaist-mistral-orpo-OHP-15k-Mathcode-2epoch-ohp-15k-strat-1-1epoch | null | [
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"base_model:orpo-explorers/kaist-mistral-orpo-OHP-15k-Mathcode-2epoch",
"autotrain_compa... | null | 2024-04-27T14:18:00+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #mistral #text-generation #alignment-handbook #trl #orpo #generated_from_trainer #conversational #dataset-orpo-explorers/OHP-15k-Stratified-1 #base_model-orpo-explorers/kaist-mistral-orpo-OHP-15k-Mathcode-2epoch #autotrain_compatible #endpoints_compatible #text-generation-in... |
# kaist-mistral-orpo-OHP-15k-Mathcode-2epoch-ohp-15k-strat-1-1epoch
This model is a fine-tuned version of orpo-explorers/kaist-mistral-orpo-OHP-15k-Mathcode-2epoch on the orpo-explorers/OHP-15k-Stratified-1 dataset.
## Model description
More information needed
## Intended uses & limitations
More information nee... | [
"# kaist-mistral-orpo-OHP-15k-Mathcode-2epoch-ohp-15k-strat-1-1epoch\n\nThis model is a fine-tuned version of orpo-explorers/kaist-mistral-orpo-OHP-15k-Mathcode-2epoch on the orpo-explorers/OHP-15k-Stratified-1 dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore... | [
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text-generation | transformers | # Prodigy SM Base v0.1
<img src="https://cdn-uploads.huggingface.co/production/uploads/617bbeec14572ebe9e6ea83f/4p2zaOWu6kTS3fcbevHef.png" width="70%" height="70%">
In our latest endeavour, we performed continued pre-training of a large language model (Mistral-7b-v0.1) to understand and generate text in new languages... | {"language": ["en", "sr", "hr", "bs"], "license": "apache-2.0"} | draganjovanovich/prodigy-sm-base-v0.1 | null | [
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"mistral",
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"license:apache-2.0",
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"endpoints_compatible",
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] | null | 2024-04-27T14:20:14+00:00 | [
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| # Prodigy SM Base v0.1
<img src="URL width="70%" height="70%">
In our latest endeavour, we performed continued pre-training of a large language model (Mistral-7b-v0.1) to understand and generate text in new languages, including Serbian, Bosnian and Croatian using an innovative approach.
Rather than depending only o... | [
"# Prodigy SM Base v0.1\n\n<img src=\"URL width=\"70%\" height=\"70%\">\n\nIn our latest endeavour, we performed continued pre-training of a large language model (Mistral-7b-v0.1) to understand and generate text in new languages, including Serbian, Bosnian and Croatian using an innovative approach. \n\nRather than ... | [
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Boya1_RMSProp_1-e5_10Epoch_swinv2-small-patch4-window16-256_fold1
This model is a fine-tuned version of [microsoft/swinv2-small-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swinv2-small-patch4-window16-256", "model-index": [{"name": "Boya1_RMSProp_1-e5_10Epoch_swinv2-small-patch4-window16-256_fold1", "results": [{"task": {"type": "image-classificatio... | onizukal/Boya1_RMSProp_1-e5_10Epoch_swinv2-small-patch4-window16-256_fold1 | null | [
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| Boya1\_RMSProp\_1-e5\_10Epoch\_swinv2-small-patch4-window16-256\_fold1
======================================================================
This model is a fine-tuned version of microsoft/swinv2-small-patch4-window16-256 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-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* lr\\_scheduler\\_warmup\\_ratio: ... | [
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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="saousan/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional att... | {"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": ... | saousan/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:23:06+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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] |
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="Astowny/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional att... | {"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": ... | Astowny/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:24:24+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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] |
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="SarahDhrifa/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": ... | SarahDhrifa/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:24:38+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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] |
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="toure32/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional att... | {"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": ... | toure32/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:25:07+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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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
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-Documentation/
... | {"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]} | Unclad3610/ppo-Huggy | null | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | null | 2024-04-27T14:26:11+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
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* where you te... | [
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* wh... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shallow6414/wgxfn2k | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T14:26:14+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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="FitTechMike/Taxi-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": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.52 +/- ... | FitTechMike/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:26:33+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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] |
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="Yann2310/CrazyTaxi", 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": "CrazyTaxi", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/... | Yann2310/CrazyTaxi | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:27:24+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 | null |
# hus960/FrankenLlama-3-12B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from [`mlabonne/FrankenLlama-3-12B-Instruct`](https://huggingface.co/mlabonne/FrankenLlama-3-12B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [... | {"license": "other", "tags": ["merge", "mergekit", "lazymergekit", "llama-cpp", "gguf-my-repo"], "base_model": ["meta-llama/Meta-Llama-3-8B-Instruct", "meta-llama/Meta-Llama-3-8B-Instruct"]} | hus960/FrankenLlama-3-12B-Instruct-Q4_K_M-GGUF | null | [
"gguf",
"merge",
"mergekit",
"lazymergekit",
"llama-cpp",
"gguf-my-repo",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:other",
"region:us"
] | null | 2024-04-27T14:27:27+00:00 | [] | [] | TAGS
#gguf #merge #mergekit #lazymergekit #llama-cpp #gguf-my-repo #base_model-meta-llama/Meta-Llama-3-8B-Instruct #license-other #region-us
|
# hus960/FrankenLlama-3-12B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from 'mlabonne/FrankenLlama-3-12B-Instruct' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.... | [
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"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL se... | [
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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="saousan/taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
e... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- ... | saousan/taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:27:29+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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] |
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="Astowny/taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
e... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.54 +/- ... | Astowny/taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:27:30+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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] |
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="SarahDhrifa/taxi-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": "taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.52 +/- ... | SarahDhrifa/taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:27:36+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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] |
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="brunel/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attr... | {"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": ... | brunel/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:27:47+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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] |
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="toure32/Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
e... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.52 +/- ... | toure32/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:27:51+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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] |
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="SamirLahouar/Taxi-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": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- ... | SamirLahouar/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:29:01+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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] |
text-generation | transformers |
# OpenAI GPT-2 Samsum
## Model description
This model has been trained with the SAMSum dataset. The SAMSum dataset contains approximately 16,000 conversational dialogues accompanied by summaries. These conversations were created and written by linguists proficient in fluent English. Linguists were instructed to crea... | {"language": ["en"], "datasets": ["samsum"], "pipeline_tag": "text-generation"} | anezatra/gpt2-samsum-124M | null | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"en",
"dataset:samsum",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T14:29:14+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #gpt2 #text-generation #en #dataset-samsum #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# OpenAI GPT-2 Samsum
## Model description
This model has been trained with the SAMSum dataset. The SAMSum dataset contains approximately 16,000 conversational dialogues accompanied by summaries. These conversations were created and written by linguists proficient in fluent English. Linguists were instructed to crea... | [
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unconditional-image-generation | diffusers |
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('ljw20180420/sd-class-butter... | {"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]} | ljw20180420/sd-class-butterflies-32 | null | [
"diffusers",
"safetensors",
"pytorch",
"unconditional-image-generation",
"diffusion-models-class",
"license:mit",
"diffusers:DDPMPipeline",
"region:us"
] | null | 2024-04-27T14:30:20+00:00 | [] | [] | TAGS
#diffusers #safetensors #pytorch #unconditional-image-generation #diffusion-models-class #license-mit #diffusers-DDPMPipeline #region-us
|
# Model Card for Unit 1 of the Diffusion Models Class
This model is a diffusion model for unconditional image generation of cute .
## Usage
'''python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('ljw20180420/sd-class-butterflies-32')
image = pipeline().images[0]
image
| [
"# Model Card for Unit 1 of the Diffusion Models Class \n\nThis model is a diffusion model for unconditional image generation of cute .",
"## Usage\n\n'''python\nfrom diffusers import DDPMPipeline\n\npipeline = DDPMPipeline.from_pretrained('ljw20180420/sd-class-butterflies-32')\nimage = pipeline().images[0]\nimag... | [
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text-generation | transformers |
# Llama-3-Ko-OpenOrca
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
Original model: [beomi/Llama-3-Open-Ko-8B](https://huggingface.co/beomi/Llama-3-Open-Ko-8B)
Dataset: [kyujinpy/OpenOrca-KO](https://h... | {"license": "llama3", "library_name": "transformers", "datasets": ["kyujinpy/OpenOrca-KO"], "pipeline_tag": "text-generation"} | werty1248/Llama-3-Ko-8B-OpenOrca | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"dataset:kyujinpy/OpenOrca-KO",
"license:llama3",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T14:30:51+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #dataset-kyujinpy/OpenOrca-KO #license-llama3 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Llama-3-Ko-OpenOrca
## Model Details
### Model Description
Original model: beomi/Llama-3-Open-Ko-8B
Dataset: kyujinpy/OpenOrca-KO
### Training details
Training: Axolotl을 이용해 LoRA-8bit로 4epoch 학습 시켰습니다.
- sequence_len: 4096
- bf16
학습 시간: A6000x2, 6시간
### Evaluation
- 0 shot kobest
| Tasks ... | [
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"### Evaluation\n\n- 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="brunel/taxi-v4", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
en... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "taxi-v4", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- ... | brunel/taxi-v4 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-27T14:30:55+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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] |
text-generation | transformers |
# Uploaded model
- **Developed by:** ramixpe
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/m... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | ramixpe/llama3-8b-SP_IOSXR | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"sft",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-27T14:33:48+00:00 | [] | [
"en"
] | TAGS
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|
# Uploaded model
- Developed by: ramixpe
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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null | transformers |
# hus960/Llama-3-13B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from [`Replete-AI/Llama-3-13B-Instruct`](https://huggingface.co/Replete-AI/Llama-3-13B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model ca... | {"license": "other", "library_name": "transformers", "tags": ["llama-cpp", "gguf-my-repo"], "base_model": [], "license_name": "llama-3", "license_link": "https://llama.meta.com/llama3/license/"} | hus960/Llama-3-13B-Instruct-Q4_K_M-GGUF | null | [
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# hus960/Llama-3-13B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from 'Replete-AI/Llama-3-13B-Instruct' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Se... | [
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text2text-generation | transformers | Question:
- Encoder: ViT5-base
- Max length: 32
- Pre-Processing: lower, remove special character
Image:
- Encoder: VIT-base
- Pre-Processing: None
OCR:
- Text Detection: Paddle OCR
- Text Recognition: VietOCR
- Threshold: 0.8
- Max length: 128
- Post-processing: group layout, divide=4
Answer:
- Max length: 56
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- Pre-Processing: lower, remove special character
Image:
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OCR:
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- Max length: 56
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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
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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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
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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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text-generation | transformers |
# Model Card for Model ID
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text-generation | transformers |
**This is a quantized version of HF's [StarChat2 15B v0.1](iHuggingFaceH4/starchat2-15b-v0.1) (see below).**
**Quantization done with [AutoAWQ](https://github.com/casper-hansen/AutoAWQ/).**
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Quantization done with AutoAWQ.
<img src="URL alt="StarChat2 15B Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
Model Card for StarChat2 15B
============================
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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": []} | erfanzar/Xerxes-8B-Instruct-v0.4 | 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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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": []} | EmnaFazaa/donut-financial-document-classification | 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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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
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-Documentati... | {"library_name": "ml-agents", "tags": ["Pyramids", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | ed-butcher/ppo-PyramidsRND | null | [
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|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids
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:
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text-generation | transformers |
# Uploaded model
- **Developed by:** bingogogogo
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | bingogogogo/llama3-8b-oig-unsloth-merged | null | [
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# Uploaded model
- Developed by: bingogogogo
- License: apache-2.0
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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": []} | MohammadKarami/hard-bert | null | [
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"arxiv:1910.09700",
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# Model Card for Model ID
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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 | null |
This model has been pushed to the Hub using ****:
- Repo: [More Information Needed]
- Docs: [More Information Needed] | {"tags": ["pytorch_model_hub_mixin", "model_hub_mixin"]} | JacobAndersson/test-publish | null | [
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null | transformers |
# hus960/Prima-LelantaclesV7-experimentalv2-7b-Q4_K_M-GGUF
This model was converted to GGUF format from [`Nitral-AI/Prima-LelantaclesV7-experimentalv2-7b`](https://huggingface.co/Nitral-AI/Prima-LelantaclesV7-experimentalv2-7b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/ggu... | {"license": "other", "library_name": "transformers", "tags": ["mergekit", "merge", "llama-cpp", "gguf-my-repo"], "base_model": ["tavtav/eros-7b-test", "ChaoticNeutrals/Prima-LelantaclesV7-experimental-7b"]} | hus960/Prima-LelantaclesV7-experimentalv2-7b-Q4_K_M-GGUF | null | [
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] | null | 2024-04-27T14:49:23+00:00 | [] | [] | TAGS
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|
# hus960/Prima-LelantaclesV7-experimentalv2-7b-Q4_K_M-GGUF
This model was converted to GGUF format from 'Nitral-AI/Prima-LelantaclesV7-experimentalv2-7b' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the U... | [
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null | transformers |
# Uploaded model
- **Developed by:** bingogogogo
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | bingogogogo/llama3-8b-oig-unsloth | null | [
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|
# Uploaded model
- Developed by: bingogogogo
- License: apache-2.0
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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. -->
# 0.001_5iters_bs256_nodpo_only4w_iter_4
This model is a fine-tuned version of [ShenaoZhang/0.001_5iters_bs256_nodpo_only4w_iter_3... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.001_5iters_bs256_nodpo_only4w_iter_3", "model-index": [{"name": "0.001_5iters_bs256_nodpo_only4w_iter_4", "results": []}]} | ShenaoZhang/0.001_5iters_bs256_nodpo_only4w_iter_4 | null | [
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# 0.001_5iters_bs256_nodpo_only4w_iter_4
This model is a fine-tuned version of ShenaoZhang/0.001_5iters_bs256_nodpo_only4w_iter_3 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More i... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shallow6414/8axzvq4 | 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]:
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- Model type:
- Language(s) (NLP):
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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. -->
# Falcon-7b-Finetuned-MBPP-Dataset-base
This model is a fine-tuned version of [tiiuae/falcon-7b-instruct](https://huggingface.co/t... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "tiiuae/falcon-7b-instruct", "model-index": [{"name": "Falcon-7b-Finetuned-MBPP-Dataset-base", "results": []}]} | MUsama100/Falcon-7b-Finetuned-MBPP-Dataset-base | null | [
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| Falcon-7b-Finetuned-MBPP-Dataset-base
=====================================
This model is a fine-tuned version of tiiuae/falcon-7b-instruct on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9306
Model description
-----------------
More information needed
Intended uses &... | [
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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": []} | khairi/ProtNLA_t12x12_terms_tmp | 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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null | null | <!-- 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/Llama-3-8B-Web-GGUF-smashed | null | [
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#gguf #pruna-ai #region-us
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[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
This repo contains GGUF versions of the McGill-NLP/Llama-3-8B-Web model.
------------------------------------------------------------------------
Simply make AI models cheaper, smaller, faster, and greener!
========... | [
"### How to load this model in Python code, using llama-cpp-python\n\nFor full documentation, please see: llama-cpp-python docs.",
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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": []} | AyoubELFallah/SEBN | null | [
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null | transformers |
# hus960/Lelanta-lake-7b-Q4_K_M-GGUF
This model was converted to GGUF format from [`Nitral-AI/Lelanta-lake-7b`](https://huggingface.co/Nitral-AI/Lelanta-lake-7b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggi... | {"license": "other", "library_name": "transformers", "tags": ["mergekit", "merge", "llama-cpp", "gguf-my-repo"], "base_model": ["s3nh/SeverusWestLake-7B-DPO", "ChaoticNeutrals/Prima-LelantaclesV7-experimental-7b"]} | hus960/Lelanta-lake-7b-Q4_K_M-GGUF | null | [
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|
# hus960/Lelanta-lake-7b-Q4_K_M-GGUF
This model was converted to GGUF format from 'Nitral-AI/Lelanta-lake-7b' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
No... | [
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text-generation | transformers |
# Orpo-Phi3-3B-128K
This is an ORPO fine-tune of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on 10k samples of [mlabonne/orpo-dpo-mix-40k](https... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["orpo", "Phi 3"], "datasets": ["mlabonne/orpo-dpo-mix-40k"], "base_model": ["microsoft/Phi-3-mini-128k-instruct"]} | Muhammad2003/Orpo-Phi3-3B-128K | null | [
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|
# Orpo-Phi3-3B-128K
!image/jpeg
This is an ORPO fine-tune of microsoft/Phi-3-mini-128k-instruct on 10k samples of mlabonne/orpo-dpo-mix-40k.
## Usage
## Training curves
Wandb Report
!image/png
## Evaluation
Coming Soon! | [
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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": []} | efeno/llama3_finetuned | null | [
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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 |
# 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": []} | hilaltekgoz/tr_paraphrase_t5 | 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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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. -->
# bart_CNN_NLP
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on ... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "facebook/bart-large-cnn", "model-index": [{"name": "bart_CNN_NLP", "results": []}]} | Moatasem22/bart_CNN_NLP | null | [
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"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-27T15:15:34+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bart #text2text-generation #generated_from_trainer #base_model-facebook/bart-large-cnn #license-mit #autotrain_compatible #endpoints_compatible #region-us
| bart\_CNN\_NLP
==============
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 3.0479
* Rouge1: 45.8751
* Rouge2: 28.1917
* Rougel: 42.0922
* Rougelsum: 41.9934
* Gen Len: 6433791.8333
Model description
------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\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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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": []} | efeno/llama3_finetuned_tokenizer | null | [
"transformers",
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#transformers #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.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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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": []} | golf2248/mf87mbi | 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-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": []} | vkimbris/messages-analyzer-multilabel | 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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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="konawa/konawa_Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False et... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "konawa_Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.... | konawa/konawa_Taxi-v3 | null | [
"Taxi-v3",
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"custom-implementation",
"model-index",
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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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] |
null | null |
## Responsible AI Considerations
Like other language models, the Phi series models can potentially behave in ways that are unfair, unreliable, or offensive. Some of the limiting behaviors to be aware of include:
Quality of Service:
The Phi models are primarily trained on English text. Languages other than English ... | {"language": ["it"], "license": "mit"} | Antonio88/PHI3STRAN-128K-ITA-V.0.1-Q5_K_M.GGUF | null | [
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#gguf #it #license-mit #region-us
|
## Responsible AI Considerations
Like other language models, the Phi series models can potentially behave in ways that are unfair, unreliable, or offensive. Some of the limiting behaviors to be aware of include:
Quality of Service:
The Phi models are primarily trained on English text. Languages other than English ... | [
"## Responsible AI Considerations\n\nLike other language models, the Phi series models can potentially behave in ways that are unfair, unreliable, or offensive. Some of the limiting behaviors to be aware of include:\n\nQuality of Service:\nThe Phi models are primarily trained on English text. Languages other than E... | [
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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. -->
# my_eli5_clm_model
This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-ba... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["eli5_category"], "base_model": "google-bert/bert-base-cased", "model-index": [{"name": "my_eli5_clm_model", "results": []}]} | ljgries/my_eli5_clm_model | null | [
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"safetensors",
"bert",
"text-generation",
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"dataset:eli5_category",
"base_model:google-bert/bert-base-cased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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#transformers #tensorboard #safetensors #bert #text-generation #generated_from_trainer #dataset-eli5_category #base_model-google-bert/bert-base-cased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# my_eli5_clm_model
This model is a fine-tuned version of google-bert/bert-base-cased on the eli5_category dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training h... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shallow6414/klcf6l6 | null | [
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# Model Card for Model ID
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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": []} | JacobAndersson/slimed-mistral-1 | null | [
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null | null | <!-- 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/Unichat-llama3-Chinese-8B-GGUF-smashed | null | [
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[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
This repo contains GGUF versions of the UnicomLLM/Unichat-llama3-Chinese-8B model.
----------------------------------------------------------------------------------
Simply make AI models cheaper, smaller, faster, a... | [
"### How to load this model in Python code, using llama-cpp-python\n\nFor full documentation, please see: llama-cpp-python docs.",
"#### First install the package\n\nRun one of the following commands, according to your system:",
"#### Simple llama-cpp-python example code\n\n```\n\n* Option D - Running with Lang... | [
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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": []} | JacobAndersson/slimed-mistral-2 | 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]:
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Boya1_RMSProp_1-e5_10Epoch_swinv2-large-patch4_fold3
This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft", "model-index": [{"name": "Boya1_RMSProp_1-e5_10Epoch_swinv2-large-patch4_fold3", "results": [{"task": {"type": "image-classi... | onizukal/Boya1_RMSProp_1-e5_10Epoch_swinv2-large-patch4_fold3 | null | [
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| Boya1\_RMSProp\_1-e5\_10Epoch\_swinv2-large-patch4\_fold3
=========================================================
This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8858... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-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* lr\\_scheduler\\_warmup\\_ratio: ... | [
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text-generation | transformers |
gobean: This was downloaded from source on release day. It's the only set of weights I trust to be equal to the original release.
<p style="font-size:20px;" align="center">
🏠 <a href="https://wizardlm.github.io/WizardLM2" target="_blank">WizardLM-2 Release Blog</a> </p>
<p align="center">
🤗 <a href="https://huggin... | {"license": "apache-2.0"} | gobean/WizardLM-2-7B | null | [
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|
gobean: This was downloaded from source on release day. It's the only set of weights I trust to be equal to the original release.
<p style="font-size:20px;" align="center">
<a href="URL target="_blank">WizardLM-2 Release Blog</a> </p>
<p align="center">
<a href="URL target="_blank">HF Repo</a> • <a href="URL targ... | [
"## News [2024/04/15]\n\nWe introduce and opensource WizardLM-2, our next generation state-of-the-art large language models, \nwhich have improved performance on complex chat, multilingual, reasoning and agent. \nNew family includes three cutting-edge models: WizardLM-2 8x22B, WizardLM-2 70B, and WizardLM-2 7B.\n\... | [
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text-generation | null |
## Exllama v2 Quantizations of Phi-3-mini-128k-instruct
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.20">turboderp's ExLlamaV2 v0.0.20</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branc... | {"language": ["en"], "license": "mit", "tags": ["nlp", "code"], "license_link": "https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/LICENSE", "pipeline_tag": "text-generation", "widget": [{"messages": [{"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?... | bartowski/Phi-3-mini-128k-instruct-exl2 | null | [
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|
## Exllama v2 Quantizations of Phi-3-mini-128k-instruct
Using <a href="URL ExLlamaV2 v0.0.20</a> for quantization.
<b>The "main" branch only contains the URL, download one of the other branches for the model (see below)</b>
Each branch contains an individual bits per weight, with the main one containing only the UR... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# LoRA text2image fine-tuning - zabibeau/onepiece-lora
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5.... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "diffusers-training", "lora", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "diffusers-training", "lora"], "base_model": "runwayml/... | zabibeau/onepiece-lora | null | [
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|
# LoRA text2image fine-tuning - zabibeau/onepiece-lora
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the YaYaB/onepiece-blip-captions dataset. You can find some example images in the following.
!img_0
!img_1
!img_2
!img_3
## 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. -->
# zephyr-7b-gemma-hinge
This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-gemma-sft-v0.1](https://huggingface.co/Hugg... | {"license": "other", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["argilla/dpo-mix-7k"], "base_model": "HuggingFaceH4/zephyr-7b-gemma-sft-v0.1", "model-index": [{"name": "zephyr-7b-gemma-hinge", "results": []}]} | chrlu/zephyr-7b-gemma-hinge | null | [
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| zephyr-7b-gemma-hinge
=====================
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-gemma-sft-v0.1 on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5273
* Rewards/chosen: -2.6335
* Rewards/rejected: -3.8935
* Rewards/accuracies: 0.7292
* Rew... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 4\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 8\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 128\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. -->
# Training
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1"], "base_model": "bert-base-cased", "model-index": [{"name": "Training", "results": []}]} | rohanphadke/bert-finetune-test | null | [
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"region:us"
] | null | 2024-04-27T15:42:06+00:00 | [] | [] | TAGS
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| Training
========
This model is a fine-tuned version of bert-base-cased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1474
* Precision: 0.9421
* Recall: 0.8978
* F1: 0.9194
* Roc Auc: 0.9859
* Krippendorff Alpha: 0.8754
Model description
-----------------
More informati... | [
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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": []} | presencesw/mt5-base-snli-cross | null | [
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"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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- Funded by [optional]:
- Shared by [optional]:
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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": []} | rPucs/gemma-2b-itTripletDolly-WebNLG-tests | 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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