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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. -->
# ModelTrainingESP-3000SamplesV1
This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://hugging... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "dccuchile/distilbert-base-spanish-uncased", "model-index": [{"name": "ModelTrainingESP-3000SamplesV1", "results": []}]} | RagnellRks/ModelTrainingESP-3000SamplesV1 | null | [
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|
# ModelTrainingESP-3000SamplesV1
This model is a fine-tuned version of dccuchile/distilbert-base-spanish-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1368
- Accuracy: 0.9567
- F1: 0.9568
## Model description
More information needed
## Intended uses & limitatio... | [
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text-to-image | diffusers |
# LoRA DreamBooth - squaadinc/1712834245926x115018013657796290
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
```
TOK
```
Use this keyword to trigger your custom model in your prompts.
LoRA for ... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["diper/Modelo_Marketing_Moda"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "TOK", "inference": false} | squaadinc/1712834245926x115018013657796290 | null | [
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"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
] | null | 2024-04-11T11:17:38+00:00 | [] | [] | TAGS
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|
# LoRA DreamBooth - squaadinc/1712834245926x115018013657796290
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
Use this keyword to trigger your custom model in your prompts.
LoRA for the text en... | [
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text-generation | null |
## Llamacpp Quantizations of Chat2DB-SQL-7B
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2636">b2636</a> for quantization.
Original model: https://huggingface.co/Chat2DB/Chat2DB-SQL-7B
All quants made using imatrix option... | {"language": ["zh", "en"], "license": "apache-2.0", "pipeline_tag": "text-generation", "quantized_by": "bartowski"} | bartowski/Chat2DB-SQL-7B-GGUF | null | [
"gguf",
"text-generation",
"zh",
"en",
"license:apache-2.0",
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#gguf #text-generation #zh #en #license-apache-2.0 #region-us
| Llamacpp Quantizations of Chat2DB-SQL-7B
----------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
-------------
No chat template specified so default is used.... | [] | [
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null | null | Introduzione:
L'alluce valgo, comunemente noto come alluce valgo, è una condizione dolorosa che colpisce l'articolazione dell'alluce. Sebbene siano disponibili varie opzioni di trattamento, una delle soluzioni meno conosciute ma efficaci è ValGone crema Cream. In questo articolo approfondiremo cos'è la Crema ValGone g... | {"license": "apache-2.0"} | ValGone-Italy/ValGone-Italy | null | [
"license:apache-2.0",
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#license-apache-2.0 #region-us
| Introduzione:
L'alluce valgo, comunemente noto come alluce valgo, è una condizione dolorosa che colpisce l'articolazione dell'alluce. Sebbene siano disponibili varie opzioni di trattamento, una delle soluzioni meno conosciute ma efficaci è ValGone crema Cream. In questo articolo approfondiremo cos'è la Crema ValGone g... | [] | [
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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. -->
# finetuned-facebook-bart-samsum
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/b... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "facebook/bart-large-cnn", "model-index": [{"name": "finetuned-facebook-bart-samsum", "results": []}]} | codebasics/finetuned-facebook-bart-samsum | null | [
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|
# finetuned-facebook-bart-samsum
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training... | [
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null | null | github: https://github.com/eteced/arithmetic_finetuning_v1 | {"license": "gpl-3.0"} | eteced/ArthModel | null | [
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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. -->
# mistralv1_dora_r24_1e6
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistra... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "mistralv1_dora_r24_1e6", "results": []}]} | fangzhaoz/mistralv1_dora_r24_1e6 | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | null | 2024-04-11T11:28:36+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #generated_from_trainer #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us
|
# mistralv1_dora_r24_1e6
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperpa... | [
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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": []} | fangzhaoz/mistralv1_dora_r24_1e6_merged | 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 Description
**bert-base-german-cased_cimt-argument-type** is a fine-tuned BERT model that is built to predict the type of an argumentative sentence. It has been trained to recognize two classes: major position (LABEL_1) and premise (LABEL_0).
Specifically, this model is a *bert-base-german-cased* that was f... | {"language": ["de"], "license": "cc-by-nc-sa-4.0", "tags": ["public participation", "text classification", "argument mining"]} | juliaromberg/bert-base-german-cased_cimt-argument-type | null | [
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## Model Description
bert-base-german-cased_cimt-argument-type is a fine-tuned BERT model that is built to predict the type of an argumentative sentence. It has been trained to recognize two classes: major position (LABEL_1) and premise (LABEL_0).
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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": []} | Spruteus/Spruteus-ft | null | [
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# Model Card for Model ID
## Model Details
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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. -->
# brev-translator
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/M... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "TheBloke/Mistral-7B-Instruct-v0.2-GPTQ", "model-index": [{"name": "brev-translator", "results": []}]} | Spruteus/brev-translator | null | [
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===============
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.5848
Model description
-----------------
More information needed
Intended uses & limitations
------------------... | [
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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. -->
# curso_hgface_sesion_1
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unkn... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-cased", "model-index": [{"name": "curso_hgface_sesion_1", "results": []}]} | fjml2014tic/curso_hgface_sesion_1 | null | [
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#transformers #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-cased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# curso_hgface_sesion_1
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
... | [
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null | transformers |
# 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": []} | Reihaneh/wav2vec2_germanic_common_voice_4 | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T11:33:13+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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feature-extraction | 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. -->
# finetuned_bge_ver6
This model is a fine-tuned version of [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3) on an unknown dataset... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "BAAI/bge-m3", "model-index": [{"name": "finetuned_bge_ver6", "results": []}]} | comet24082002/finetuned_bge_ver6 | null | [
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"feature-extraction",
"generated_from_trainer",
"base_model:BAAI/bge-m3",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T11:36:57+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #xlm-roberta #feature-extraction #generated_from_trainer #base_model-BAAI/bge-m3 #license-mit #endpoints_compatible #region-us
|
# finetuned_bge_ver6
This model is a fine-tuned version of BAAI/bge-m3 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The fo... | [
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"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Tr... | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | dallonf/ppo-LunarLander-v2-rlcourse | null | [
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"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-11T11:37:32+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Mixt... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["moe"], "base_model": "mistral-community/Mixtral-8x22B-v0.1", "quantized_by": "mradermacher"} | mradermacher/Mixtral-8x22B-v0.1-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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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-samsum-finetuned
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-l... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "facebook/bart-large-cnn", "model-index": [{"name": "bart-cnn-samsum-finetuned", "results": []}]} | Chirantan2/bart-cnn-samsum-finetuned | null | [
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"license:mit",
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"endpoints_compatible",
"region:us"
] | null | 2024-04-11T11:42:29+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-samsum-finetuned
=========================
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1578
Model description
-----------------
More information needed
Intended uses & limitations
-------------... | [
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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"]} | AGI-CEO/ppo-Huggy | null | [
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"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | null | 2024-04-11T11:43:03+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... | [
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null | 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. -->
# donut-base-pdfs
This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-ba... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "naver-clova-ix/donut-base", "model-index": [{"name": "donut-base-pdfs", "results": []}]} | savankamahina/donut-base-pdfs | null | [
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"vision-encoder-decoder",
"generated_from_trainer",
"base_model:naver-clova-ix/donut-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T11:45:11+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #vision-encoder-decoder #generated_from_trainer #base_model-naver-clova-ix/donut-base #license-mit #endpoints_compatible #region-us
|
# donut-base-pdfs
This model is a fine-tuned version of naver-clova-ix/donut-base on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameter... | [
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image-to-text | transformers |
# Model Card
HuggingFaceH4/vsft-llava-1.5-7b-hf-trl is a Vision Language Model, created by performing VSFT on the [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf) model wit... | {"language": ["en"], "datasets": ["HuggingFaceH4/llava-instruct-mix-vsft"], "pipeline_tag": "image-to-text", "inference": false, "arxiv": 2304.08485} | HuggingFaceH4/vsft-llava-1.5-7b-hf-trl | null | [
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"llava",
"pretraining",
"image-to-text",
"en",
"dataset:HuggingFaceH4/llava-instruct-mix-vsft",
"has_space",
"region:us"
] | null | 2024-04-11T11:45:35+00:00 | [] | [
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#transformers #safetensors #llava #pretraining #image-to-text #en #dataset-HuggingFaceH4/llava-instruct-mix-vsft #has_space #region-us
|
!image/png
# Model Card
HuggingFaceH4/vsft-llava-1.5-7b-hf-trl is a Vision Language Model, created by performing VSFT on the llava-hf/llava-1.5-7b-hf model with 260k image and conversation pairs from the HuggingFaceH4/llava-instruct-mix-vsft dataset.
Check out our Spaces demo! ![Open in Spaces](URL
## Model details... | [
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text-classification | bertopic |
# impf_ukrain_postcov_all_sns_topics_umap_lok_hdbscan_lok_ctfidf_seed_8_prob
This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
## Usage
To use this model... | {"library_name": "bertopic", "tags": ["bertopic"], "pipeline_tag": "text-classification"} | RolMax/impf_ukrain_postcov_all_sns_topics_umap_lok_hdbscan_lok_ctfidf_seed_8_prob | null | [
"bertopic",
"text-classification",
"region:us"
] | null | 2024-04-11T11:46:35+00:00 | [] | [] | TAGS
#bertopic #text-classification #region-us
| impf\_ukrain\_postcov\_all\_sns\_topics\_umap\_lok\_hdbscan\_lok\_ctfidf\_seed\_8\_prob
=======================================================================================
This is a BERTopic model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable t... | [] | [
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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": []} | Reihaneh/wav2vec2_germanic_common_voice_6 | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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token-classification | transformers |
## Model Description
**bert-base-german-cased_cimt-location** is a fine-tuned BERT model that is built to predict location phrases using the B(beginning, LABEL_2)-I(inside, LABEL_1)-O(outside, LABEL_0) label schema.
Specifically, this model is a *bert-base-german-cased* that was fine-tuned on https://github.com/juli... | {"language": ["de"], "license": "cc-by-nc-sa-4.0", "tags": ["public participation", "text-based geo-location", "sequence labeling"]} | juliaromberg/bert-base-german-cased_cimt-location | null | [
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"region:us"
] | null | 2024-04-11T11:52:07+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #bert #token-classification #public participation #text-based geo-location #sequence labeling #de #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
## Model Description
bert-base-german-cased_cimt-location is a fine-tuned BERT model that is built to predict location phrases using the B(beginning, LABEL_2)-I(inside, LABEL_1)-O(outside, LABEL_0) label schema.
Specifically, this model is a *bert-base-german-cased* that was fine-tuned on URL
## Background
This wo... | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | IMENMANSOUR/dqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-11T11:53:49+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
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text-generation | transformers | # experiment_37
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 linear [DARE](https://arxiv.org/abs/2311.03099) merge method using [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/Huggin... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Aaryan-Nakhat/experiment-31-prompt-5-guardrails-finetuning-itr-4-sub-prompt-1", "Aaryan-Nakhat/experiment-32-prompt-5-guardrails-finetuning-itr-4-sub-prompt-2", "HuggingFaceH4/zephyr-7b-beta"]} | Aaryan-Nakhat/experiment-37-prompt-5-guardrails-finetuning-itr-4-merged-exp-31-32 | null | [
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"base_model:Aaryan-Nakhat/experiment-32-prompt-5-guardrails-finetuning-itr-4-sub-promp... | null | 2024-04-11T11:54:09+00:00 | [
"2311.03099"
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This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the linear DARE merge method using HuggingFaceH4/zephyr-7b-beta as a base.
### Models Merged
The following models were included in the merge:
* Aaryan-Nakhat/experime... | [
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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": []} | tomaszki/stablelm-25 | null | [
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"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T11:56:59+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-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": []} | tomaszki/stablelm-25-a | null | [
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"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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"1910.09700"
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#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/CultriX/AlphaCeption-7B-v1
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show ... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "CultriX/AlphaCeption-7B-v1", "quantized_by": "mradermacher"} | mradermacher/AlphaCeption-7B-v1-GGUF | null | [
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"merge",
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"base_model:CultriX/AlphaCeption-7B-v1",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T11:59:23+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #mergekit #merge #en #base_model-CultriX/AlphaCeption-7B-v1 #license-apache-2.0 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Dhara3078/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-11T12:00:42+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
text-generation | transformers | # experiment_38
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/Huggin... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Aaryan-Nakhat/experiment-32-prompt-5-guardrails-finetuning-itr-4-sub-prompt-2", "HuggingFaceH4/zephyr-7b-beta", "Aaryan-Nakhat/experiment-31-prompt-5-guardrails-finetuning-itr-4-sub-prompt-1"]} | Aaryan-Nakhat/experiment-38-prompt-5-guardrails-finetuning-itr-4-merged-exp-31-32 | null | [
"transformers",
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"mistral",
"text-generation",
"mergekit",
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"arxiv:2403.19522",
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"base_model:HuggingFaceH4/zephyr-7b-beta",
"base_model:Aaryan-Nakhat/experiment-31-p... | null | 2024-04-11T12:00:54+00:00 | [
"2403.19522"
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This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the Model Stock merge method using HuggingFaceH4/zephyr-7b-beta as a base.
### Models Merged
The following models were included in the merge:
* Aaryan-Nakhat/experime... | [
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"### Merge Method\n\nThis model was merged using the Model Stock merge method using HuggingFaceH4/zephyr-7b-beta as a base.",
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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": []} | tomaszki/stablelm-25-b | null | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T12:01:15+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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"]} | pseudoboson/ppo-SnowballTarget | null | [
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"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | null | 2024-04-11T12:02:03+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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null | mlx |
# mitkox/Mistral-22B-v0.1-4bit-MLX
This model was converted to MLX format from [`Vezora/Mistral-22B-v0.1`]() using mlx-lm version **0.6.0**.
Refer to the [original model card](https://huggingface.co/Vezora/Mistral-22B-v0.1) for more details on the model.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from ... | {"license": "apache-2.0", "tags": ["mlx"]} | mitkox/Mistral-22B-v0.1-4bit-MLX | null | [
"mlx",
"safetensors",
"mistral",
"license:apache-2.0",
"region:us"
] | null | 2024-04-11T12:03:47+00:00 | [] | [] | TAGS
#mlx #safetensors #mistral #license-apache-2.0 #region-us
|
# mitkox/Mistral-22B-v0.1-4bit-MLX
This model was converted to MLX format from ['Vezora/Mistral-22B-v0.1']() using mlx-lm version 0.6.0.
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# mitkox/Mistral-22B-v0.1-4bit-MLX\nThis model was converted to MLX format from ['Vezora/Mistral-22B-v0.1']() using mlx-lm version 0.6.0.\nRefer to the original model card for more details on the model.",
"## Use with mlx"
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"TAGS\n#mlx #safetensors #mistral #license-apache-2.0 #region-us \n# mitkox/Mistral-22B-v0.1-4bit-MLX\nThis model was converted to MLX format from ['Vezora/Mistral-22B-v0.1']() using mlx-lm version 0.6.0.\nRefer to the original model card for more details on the model.## Use with mlx"
] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | girayo/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-11T12:04:04+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... | [
31,
35,
17
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add your code"
] |
null | null | # Llama-3-8B-Instruct-Ja.gguf
alfredplpl/Llama-3-8B-Instruct-Jaのgguf版です。取り敢えずQ3KM/Q4KMをアップロードしました。
```
## 💻 Usage
プロンプトの最後に"<|eot_id|>" を付加して下さい。
詳細はalfredplpl/Llama-3-8B-Instruct-Jaを参照して下さい。 | {} | aipib/Llama-3-8B-Instruct-Ja.gguf | null | [
"gguf",
"region:us"
] | null | 2024-04-11T12:04:41+00:00 | [] | [] | TAGS
#gguf #region-us
| # URL
alfredplpl/Llama-3-8B-Instruct-Jaのgguf版です。取り敢えずQ3KM/Q4KMをアップロードしました。
'''
## Usage
プロンプトの最後に"<|eot_id|>" を付加して下さい。
詳細はalfredplpl/Llama-3-8B-Instruct-Jaを参照して下さい。 | [
"# URL\n\nalfredplpl/Llama-3-8B-Instruct-Jaのgguf版です。取り敢えずQ3KM/Q4KMをアップロードしました。\n'''",
"## Usage\n\nプロンプトの最後に\"<|eot_id|>\" を付加して下さい。\n詳細はalfredplpl/Llama-3-8B-Instruct-Jaを参照して下さい。"
] | [
"TAGS\n#gguf #region-us \n",
"# URL\n\nalfredplpl/Llama-3-8B-Instruct-Jaのgguf版です。取り敢えずQ3KM/Q4KMをアップロードしました。\n'''",
"## Usage\n\nプロンプトの最後に\"<|eot_id|>\" を付加して下さい。\n詳細はalfredplpl/Llama-3-8B-Instruct-Jaを参照して下さい。"
] | [
9,
53,
61
] | [
"TAGS\n#gguf #region-us \n# URL\n\nalfredplpl/Llama-3-8B-Instruct-Jaのgguf版です。取り敢えずQ3KM/Q4KMをアップロードしました。\n'''## Usage\n\nプロンプトの最後に\"<|eot_id|>\" を付加して下さい。\n詳細はalfredplpl/Llama-3-8B-Instruct-Jaを参照して下さい。"
] |
video-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. -->
# videomae-base-finetuned-ElderReact-Sadness12
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.c... | {"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "MCG-NJU/videomae-base", "model-index": [{"name": "videomae-base-finetuned-ElderReact-Sadness12", "results": []}]} | minhah/videomae-base-finetuned-ElderReact-Sadness12 | null | [
"transformers",
"safetensors",
"videomae",
"video-classification",
"generated_from_trainer",
"base_model:MCG-NJU/videomae-base",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T12:07:15+00:00 | [] | [] | TAGS
#transformers #safetensors #videomae #video-classification #generated_from_trainer #base_model-MCG-NJU/videomae-base #license-cc-by-nc-4.0 #endpoints_compatible #region-us
| videomae-base-finetuned-ElderReact-Sadness12
============================================
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5360
* F1: 0.0133
Model description
-----------------
More information n... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio... | [
"TAGS\n#transformers #safetensors #videomae #video-classification #generated_from_trainer #base_model-MCG-NJU/videomae-base #license-cc-by-nc-4.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train... | [
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"TAGS\n#transformers #safetensors #videomae #video-classification #generated_from_trainer #base_model-MCG-NJU/videomae-base #license-cc-by-nc-4.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_bat... |
text-generation | transformers |
# Mixtral-8x7B--v0.1: Model 8
## Model Description
This model is the 8th extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is... | {"license": "apache-2.0"} | DrNicefellow/Mistral-8-from-Mixtral-8x7B-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T12:07:43+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mixtral-8x7B--v0.1: Model 8
## Model Description
This model is the 8th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is exp... | [
"# Mixtral-8x7B--v0.1: Model 8",
"## Model Description\n\nThis model is the 8th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this mo... | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Mixtral-8x7B--v0.1: Model 8",
"## Model Description\n\nThis model is the 8th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, ... | [
42,
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66,
4,
15,
12,
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] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Mixtral-8x7B--v0.1: Model 8## Model Description\n\nThis model is the 8th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mi... |
text-generation | transformers |
# Mixtral-8x7B--v0.1: Model 7
## Model Description
This model is the 7th extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is... | {"license": "apache-2.0"} | DrNicefellow/Mistral-7-from-Mixtral-8x7B-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T12:07:45+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mixtral-8x7B--v0.1: Model 7
## Model Description
This model is the 7th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is exp... | [
"# Mixtral-8x7B--v0.1: Model 7",
"## Model Description\n\nThis model is the 7th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this mo... | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Mixtral-8x7B--v0.1: Model 7",
"## Model Description\n\nThis model is the 7th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, ... | [
42,
17,
82,
66,
4,
15,
12,
25
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Mixtral-8x7B--v0.1: Model 7## Model Description\n\nThis model is the 7th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mi... |
text-generation | transformers |
# Mixtral-8x7B--v0.1: Model 6
## Model Description
This model is the 6th extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is... | {"license": "apache-2.0"} | DrNicefellow/Mistral-6-from-Mixtral-8x7B-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T12:07:47+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mixtral-8x7B--v0.1: Model 6
## Model Description
This model is the 6th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is exp... | [
"# Mixtral-8x7B--v0.1: Model 6",
"## Model Description\n\nThis model is the 6th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this mo... | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Mixtral-8x7B--v0.1: Model 6",
"## Model Description\n\nThis model is the 6th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, ... | [
42,
17,
82,
66,
4,
15,
12,
25
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Mixtral-8x7B--v0.1: Model 6## Model Description\n\nThis model is the 6th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mi... |
text-generation | transformers |
# Mixtral-8x7B--v0.1: Model 5
## Model Description
This model is the 5th extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is... | {"license": "apache-2.0"} | DrNicefellow/Mistral-5-from-Mixtral-8x7B-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T12:07:48+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mixtral-8x7B--v0.1: Model 5
## Model Description
This model is the 5th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is exp... | [
"# Mixtral-8x7B--v0.1: Model 5",
"## Model Description\n\nThis model is the 5th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this mo... | [
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"# Mixtral-8x7B--v0.1: Model 5",
"## Model Description\n\nThis model is the 5th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, ... | [
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17,
82,
66,
4,
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12,
25
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Mixtral-8x7B--v0.1: Model 5## Model Description\n\nThis model is the 5th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mi... |
text-generation | transformers |
# Mixtral-8x7B--v0.1: Model 4
## Model Description
This model is the 4th extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is... | {"license": "apache-2.0"} | DrNicefellow/Mistral-4-from-Mixtral-8x7B-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T12:07:50+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mixtral-8x7B--v0.1: Model 4
## Model Description
This model is the 4th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is exp... | [
"# Mixtral-8x7B--v0.1: Model 4",
"## Model Description\n\nThis model is the 4th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this mo... | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Mixtral-8x7B--v0.1: Model 4",
"## Model Description\n\nThis model is the 4th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, ... | [
42,
17,
82,
66,
4,
15,
12,
25
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Mixtral-8x7B--v0.1: Model 4## Model Description\n\nThis model is the 4th extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mi... |
text-generation | transformers |
# Mixtral-8x7B--v0.1: Model 3
## Model Description
This model is the 3rd extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is... | {"license": "apache-2.0"} | DrNicefellow/Mistral-3-from-Mixtral-8x7B-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T12:07:52+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mixtral-8x7B--v0.1: Model 3
## Model Description
This model is the 3rd extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is exp... | [
"# Mixtral-8x7B--v0.1: Model 3",
"## Model Description\n\nThis model is the 3rd extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this mo... | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Mixtral-8x7B--v0.1: Model 3",
"## Model Description\n\nThis model is the 3rd extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, ... | [
42,
17,
82,
66,
4,
15,
12,
25
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Mixtral-8x7B--v0.1: Model 3## Model Description\n\nThis model is the 3rd extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mi... |
text-generation | transformers |
# Mixtral-8x7B--v0.1: Model 2
## Model Description
This model is the 2nd extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is... | {"license": "apache-2.0"} | DrNicefellow/Mistral-2-from-Mixtral-8x7B-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T12:07:54+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mixtral-8x7B--v0.1: Model 2
## Model Description
This model is the 2nd extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is exp... | [
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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": []} | zzzyj/zyj_TinyLLaMA_medical_sft | null | [
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|
# Model Card for Model ID
## Model Details
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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": []} | zzzyj/xxx_TinyLLaMA_medical_sft | null | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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": []} | AscheZ/ALIE1.3 | null | [
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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": []} | Muskan-09/finetune3 | null | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# zephyr-dpo-timedial
This model is a fine-tuned version of [EllieS/zephyr-sft-timedial](https://huggingface.co/EllieS/zephyr-sft-... | {"license": "apache-2.0", "library_name": "peft", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer"], "datasets": ["EllieS/timedial_dpo"], "base_model": "alignment-handbook/zephyr-7b-sft-full", "model-index": [{"name": "zephyr-dpo-timedial", "results": []}]} | EllieS/zephyr-dpo-timedial | null | [
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| zephyr-dpo-timedial
===================
This model is a fine-tuned version of EllieS/zephyr-sft-timedial on the EllieS/timedial\_dpo dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2236
* Rewards/chosen: 0.2987
* Rewards/rejected: -1.0958
* Rewards/accuracies: 1.0
* Rewards/margins: 1.39... | [
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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="AlidarAsvarov/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add addition... | {"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": ... | AlidarAsvarov/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-11T12:19:37+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
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] |
text-generation | transformers |
# Model 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": []} | Grayx/unstable_75 | null | [
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"arxiv:1910.09700",
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"region:us"
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"1910.09700"
] | [] | TAGS
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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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- License... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Medium GA-EN Speech Translation
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/ope... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu", "wer"], "base_model": "openai/whisper-medium", "model-index": [{"name": "Whisper Medium GA-EN Speech Translation", "results": []}]} | ymoslem/whisper-medium-ga2en-v1 | null | [
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"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:openai/whisper-medium",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T12:20:51+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #base_model-openai/whisper-medium #license-apache-2.0 #endpoints_compatible #region-us
| Whisper Medium GA-EN Speech Translation
=======================================
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.5839
* Bleu: 26.1
* Chrf: 41.83
* Wer: 74.6511
Model description
-----------------
... | [
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null | mlx |
# mlx-community/Mistral-22B-v0.1-4bit-MLX
This model was converted to MLX format from [`Vezora/Mistral-22B-v0.1`]() using mlx-lm version **0.6.0**.
Refer to the [original model card](https://huggingface.co/Vezora/Mistral-22B-v0.1) for more details on the model.
## Use with mlx
```bash
pip install mlx-lm
```
```pytho... | {"license": "apache-2.0", "tags": ["mlx"]} | mlx-community/Mistral-22B-v0.1-4bit-MLX | null | [
"mlx",
"safetensors",
"mistral",
"license:apache-2.0",
"region:us"
] | null | 2024-04-11T12:20:55+00:00 | [] | [] | TAGS
#mlx #safetensors #mistral #license-apache-2.0 #region-us
|
# mlx-community/Mistral-22B-v0.1-4bit-MLX
This model was converted to MLX format from ['Vezora/Mistral-22B-v0.1']() using mlx-lm version 0.6.0.
Refer to the original model card for more details on the model.
## Use with mlx
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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="AlidarAsvarov/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": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.50 +/- ... | AlidarAsvarov/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-11T12:21:50+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
| [
"# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
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text-classification | transformers |
## Model Description
**roberta-base-wechsel-german_cimt-transport** is a fine-tuned RoBERTa model that is built to predict modes of transport.
Specifically, this model is a *benjamin/roberta-base-wechsel-german* that was fine-tuned on two datasets of public participation for urban planning.
## Background
This work ... | {"language": ["de"], "license": "cc-by-nc-sa-4.0", "tags": ["public participation", "text classification", "transport"]} | juliaromberg/roberta-base-wechsel-german_cimt-transport | null | [
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|
## Model Description
roberta-base-wechsel-german_cimt-transport is a fine-tuned RoBERTa model that is built to predict modes of transport.
Specifically, this model is a *benjamin/roberta-base-wechsel-german* that was fine-tuned on two datasets of public participation for urban planning.
## Background
This work is b... | [
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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": []} | dp911/phi2tuned2 | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | 0x0uncle0/aunt54 | null | [
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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. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swin-tiny-patch4-window7-224", "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-eurosat", "results": [{"task": {"type": "image-classification", "name": "Image Clas... | sshreyy/swin-tiny-patch4-window7-224-finetuned-eurosat | null | [
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| swin-tiny-patch4-window7-224-finetuned-eurosat
==============================================
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4574
* Accuracy: 0.0
Model description
---------... | [
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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": []} | savinda99/roberta-hate-speech-dynabench-r4-target-finetuned-without-keywords | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tomaszki/stablelm-26 | null | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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": []} | slavalu74/code-search-net-tokenizer | null | [
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text-generation | transformers | # OGSQL-7B
### Model Description
OGSQL-7B was fine-tuned for the task of converting natural language text into SQL queries.
- **Model type**: Transformer
- **Language(s) (NLP)**: SQL (target langua... | {"language": ["en"], "license": "cc-by-4.0", "tags": ["Text-to-sql"]} | OneGate/OGSQL-7B | null | [
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| # OGSQL-7B
!image/png
### Model Description
OGSQL-7B was fine-tuned for the task of converting natural language text into SQL queries.
- Model type: Transformer
- Language(s) (NLP): SQL (target language for generation)
- Finetuned from model: gemma 7b instruct
## Use Case
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null | 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. -->
# vsft-llava-1.5-7b-hf4
This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5... | {"tags": ["trl", "sft", "generated_from_trainer"], "base_model": "llava-hf/llava-1.5-7b-hf", "model-index": [{"name": "vsft-llava-1.5-7b-hf4", "results": []}]} | edbeeching/vsft-llava-1.5-7b-hf4 | null | [
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|
# vsft-llava-1.5-7b-hf4
This model is a fine-tuned version of llava-hf/llava-1.5-7b-hf on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperpa... | [
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sentence-similarity | sentence-transformers |
# luiz-and-robert-thesis/all-mpnet-lr1e-8-margin-1-bs-32
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transfor... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | luiz-and-robert-thesis/all-mpnet-lr1e-8-margin-1-bs-32 | null | [
"sentence-transformers",
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#sentence-transformers #safetensors #mpnet #feature-extraction #sentence-similarity #endpoints_compatible #region-us
|
# luiz-and-robert-thesis/all-mpnet-lr1e-8-margin-1-bs-32
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence... | [
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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-dpo-full
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignmen... | {"license": "apache-2.0", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "alignment-handbook/zephyr-7b-sft-full", "model-index": [{"name": "zephyr-7b-dpo-full", "results": []}]} | ZHZisZZ/zephyr-7b-dpo-full | null | [
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==================
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback\_binarized dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5018
* Rewards/chosen: -1.1027
* Rewards/rejected: -2.0673
* Rewards/accuracies:... | [
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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": []} | hadiqaemi/Mistral-triples | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
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"1910.09700"
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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... | {"language": ["fr"], "library_name": "transformers"} | ApteedIA/Apteed-LLM-Instruct | 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 | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | OlejnikM/ppo-LunarLander-v2 | null | [
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"deep-reinforcement-learning",
"reinforcement-learning",
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"region:us"
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#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
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] |
null | diffusers |
# 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 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | alre5639/frontier_diff_no_cond_try_2 | null | [
"diffusers",
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"arxiv:1910.09700",
"region:us"
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"1910.09700"
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#diffusers #safetensors #arxiv-1910.09700 #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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- Model type:
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null | 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. -->
# segformer-b0-scene-parse-150
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the ... | {"license": "other", "tags": ["generated_from_trainer"], "base_model": "nvidia/mit-b0", "model-index": [{"name": "segformer-b0-scene-parse-150", "results": []}]} | koluzajka/segformer-b0-scene-parse-150 | null | [
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"base_model:nvidia/mit-b0",
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#transformers #tensorboard #safetensors #segformer #generated_from_trainer #base_model-nvidia/mit-b0 #license-other #endpoints_compatible #region-us
| segformer-b0-scene-parse-150
============================
This model is a fine-tuned version of nvidia/mit-b0 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: -34.0382
* Mean Iou: 0.0
* Mean Accuracy: nan
* Overall Accuracy: nan
* Per Category Iou: [0.0]
* Per Category Accuracy:... | [
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text-to-image | diffusers | # mbb-xl
<Gallery />
## Model description
This is the best LoRa of Millie Bobby Brown! Please download, like and give a positive review with or without your own generated images of her (only SFW) images. Some images i have uploaded are cropped to comply with TOS but will produce both SFW and NSFW images. Enjoy!! By... | {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "-", "output": {"url": "images/2024-04-10_13-37-24_6892-.jpeg"}}], "base_model": "ByteDance/SDXL-Lightning", "instance_prompt": "Millie"} | MarkBW/mbb-xl | null | [
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"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:ByteDance/SDXL-Lightning",
"region:us"
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#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-ByteDance/SDXL-Lightning #region-us
| # mbb-xl
<Gallery />
## Model description
This is the best LoRa of Millie Bobby Brown! Please download, like and give a positive review with or without your own generated images of her (only SFW) images. Some images i have uploaded are cropped to comply with TOS but will produce both SFW and NSFW images. Enjoy!! By... | [
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null | transformers | "Ctranslate2" is an amazing library that runs these models. They are faster, more accurate, and use less VRAM/RAM than GGML and GPTQ models.
How to run with instructions: https://github.com/BBC-Esq
- COMING SOON
Learn more about the amazing "ctranslate2" technology:"
- https://github.com/OpenNMT/CTranslate2
- https:... | {"tags": ["ctranslate2"]} | Startupbootcamp/Llama-2-7b-chat-ct2-int8 | null | [
"transformers",
"ctranslate2",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T12:50:48+00:00 | [] | [] | TAGS
#transformers #ctranslate2 #endpoints_compatible #region-us
| "Ctranslate2" is an amazing library that runs these models. They are faster, more accurate, and use less VRAM/RAM than GGML and GPTQ models.
How to run with instructions: URL
* COMING SOON
Learn more about the amazing "ctranslate2" technology:"
* URL
* URL
**Compatibility and Data Formats**
**Check Compa... | [] | [
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token-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. -->
# Reza-Barati/roberta-base-finetuned-for-IoC-Extracting
This model is a fine-tuned version of [roberta-base](https://huggingface.co/robe... | {"license": "mit", "tags": ["generated_from_keras_callback"], "base_model": "roberta-base", "model-index": [{"name": "Reza-Barati/roberta-base-finetuned-for-IoC-Extracting", "results": []}]} | Reza-Barati/roberta-base-finetuned-for-IoC-Extracting | null | [
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"base_model:roberta-base",
"license:mit",
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"endpoints_compatible",
"region:us"
] | null | 2024-04-11T12:51:52+00:00 | [] | [] | TAGS
#transformers #tf #tensorboard #roberta #token-classification #generated_from_keras_callback #base_model-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| Reza-Barati/roberta-base-finetuned-for-IoC-Extracting
=====================================================
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.1053
* Validation Loss: 0.0568
* Train Precision: 0.8956
* Tr... | [
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null | null | # Vezora-Mistral-22B-v0.1-gguf
[Vezoraさんが公開しているMistral-22B-v0.1](https://huggingface.co/Vezora/Mistral-22B-v0.1)のggufフォーマット変換版です。
## Usage
```
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
make -j
./main -m 'Vezora-Mistral-22B-v0.1-q4_0.gguf' -p "今夜の夕食のレシピをご紹介します。" -n 128
```
| {"language": ["en", "ja"], "license": "apache-2.0", "tags": ["mistral"]} | mmnga/Vezora-Mistral-22B-v0.1-gguf | null | [
"gguf",
"mistral",
"en",
"ja",
"license:apache-2.0",
"region:us"
] | null | 2024-04-11T12:52:56+00:00 | [] | [
"en",
"ja"
] | TAGS
#gguf #mistral #en #ja #license-apache-2.0 #region-us
| # Vezora-Mistral-22B-v0.1-gguf
Vezoraさんが公開しているMistral-22B-v0.1のggufフォーマット変換版です。
## Usage
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/wenbopan/Faro-Yi-34B
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/Faro-Yi-34B-GGUF
## ... | {"language": ["en"], "license": "mit", "library_name": "transformers", "datasets": ["wenbopan/Fusang-v1", "wenbopan/OpenOrca-zh-20k"], "base_model": "wenbopan/Faro-Yi-34B", "quantized_by": "mradermacher"} | mradermacher/Faro-Yi-34B-i1-GGUF | null | [
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| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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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": []} | she11D0n3/test_model | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-11T12:57:41+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
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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": []} | she11D0n3/test_model_1 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | 37sean/ppo-LunarLander-v2 | null | [
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"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-11T12:59:45+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whi... | {"language": ["hi"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small Hi - Sanchit Gandhi", "results": []}]} | Tejnaresh/whisper-tiny-hi | null | [
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|
# Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
#... | [
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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. -->
# wav2vec-best-CREMA-sentiment-analysis-best3
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.c... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["Supreeta03/CREMA-audioData"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "wav2vec-best-CREMA-sentiment-analysis-best3", "results": []}]} | Supreeta03/wav2vec2-base-sentiment-analysis-CREMA | null | [
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| wav2vec-best-CREMA-sentiment-analysis-best3
===========================================
This model is a fine-tuned version of facebook/wav2vec2-base on Supreeta03/CREMA-audioData.
It achieves the following results on the evaluation set:
* top2 Accuracy: 0.7824
* Loss: 1.1563
* Accuracy: 0.5601
Model description
-... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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sentence-similarity | sentence-transformers |
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | wasjaip/my_tree_model_v1_10k | null | [
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|
# {MODEL_NAME}
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
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text-classification | transformers | language: en
license: cc-by-4.0
tags:
- text-classification
repo: N.A.
---
# Model Card for llama2-promt-av-binary-lora
<!-- Provide a quick summary of what the model is/does. -->
This model is trained as part of the coursework of COMP34812.
This is a binary classification model that was trained with prompt input ... | {} | Cyrus1020/llama2-prompt-av-binary-lora | null | [
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| language: en
license: cc-by-4.0
tags:
- text-classification
repo: N.A.
---
# Model Card for llama2-promt-av-binary-lora
This model is trained as part of the coursework of COMP34812.
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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": []} | luozhuanggary/GOAT-v0.2-Mistral-7B-Teacher | null | [
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"mistral",
"text-generation",
"arxiv:1910.09700",
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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": []} | nielsr/zoedepth-nyu | null | [
"transformers",
"safetensors",
"zoedepth",
"arxiv:1910.09700",
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# Model Card for Model ID
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an un... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "facebook/bart-large-cnn", "model-index": [{"name": "results", "results": []}]} | waiman721/fine_tuned_bart-large-cnn_multi_news | null | [
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# results
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset.
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- eval_rouge1: 36.7687
- eval_rouge2: 12.7988
- eval_rougeL: 23.4116
- eval_rougeLsum: 29.7494
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text-generation | transformers |
# Uploaded model
- **Developed by:** MR-Eder
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b-bnb-4bit
This gemma 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/mai... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl", "sft"], "base_model": "unsloth/gemma-2b-bnb-4bit"} | MR-Eder/Gemma-2B-IT-WIKI-30K-v6 | null | [
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feature-extraction | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | marcus2000/rubert_pravo_demo_on_saiga | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | OneGate/OGCode | null | [
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text-generation | transformers |
# QI-neural-chat-7B-ko-DPO
This is a fine tuned model based on the [neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3) with Korean DPO dataset([Oraca-DPO-Pairs-KO](https://huggingface.co/datasets/Ja-ck/Orca-DPO-Pairs-KO)).
It processes Korean language relatively well, so it is useful when creatin... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["Korean", "LLM", "Chatbot", "DPO", "Intel/neural-chat-7b-v3-3"]} | QuantumIntelligence/QI-neural-chat-7B-ko-DPO | null | [
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|
# QI-neural-chat-7B-ko-DPO
This is a fine tuned model based on the neural-chat-7b-v3-3 with Korean DPO dataset(Oraca-DPO-Pairs-KO).
It processes Korean language relatively well, so it is useful when creating various applications.
### Basic Usage
### Using Korean
- Sentiment
- Summarization
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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. -->
# finetuned-indian-food
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vi... | {"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "datasets": ["imagefolder"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "finetuned-indian-food", "results": []}]} | Maheswari001/finetuned-indian-food | null | [
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|
# finetuned-indian-food
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the finetuned-indian-food dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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null | peft | ## Training procedure
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token-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | toghrultahirov/pii-small | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Uploaded model
- **Developed by:** MR-Eder
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b-bnb-4bit
This gemma 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/mai... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl"], "base_model": "unsloth/gemma-2b-bnb-4bit"} | MR-Eder/Gemma-2B-IT-WIKI-30K-v7 | null | [
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# layoutlm-funsd
This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["funsd"], "base_model": "microsoft/layoutlm-base-uncased", "model-index": [{"name": "layoutlm-funsd", "results": []}]} | marcoCasamento/layoutlm-funsd | null | [
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| layoutlm-funsd
==============
This model is a fine-tuned version of microsoft/layoutlm-base-uncased on the funsd dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0554
* Answer: {'precision': 0.4105691056910569, 'recall': 0.49938195302843014, 'f1': 0.45064138315672064, 'number': 809}
* Hea... | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** MR-Eder
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b-bnb-4bit
This gemma 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/mai... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl", "sft"], "base_model": "unsloth/gemma-2b-bnb-4bit"} | MR-Eder/Gemma-2B-IT-WIKI-30K-v7-16bit | null | [
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|
# Uploaded model
- Developed by: MR-Eder
- License: apache-2.0
- Finetuned from model : unsloth/gemma-2b-bnb-4bit
This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-classification | transformers |
## Model Description
**bert-base-german-cased_cimt-argument-subjectivity-4** is a fine-tuned BERT model that is built to predict how subjective annotators perceive the concreteness of argumentative utterances in urban planning processes. It has been trained to recognize 4 classes: subjective (LABEL_3), rather subject... | {"language": ["de"], "license": "cc-by-nc-sa-4.0", "tags": ["public participation", "text classification", "argument quality", "subjectivity"]} | juliaromberg/bert-base-german-cased_cimt-argument-subjectivity-4 | null | [
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#transformers #safetensors #bert #text-classification #public participation #text classification #argument quality #subjectivity #de #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
## Model Description
bert-base-german-cased_cimt-argument-subjectivity-4 is a fine-tuned BERT model that is built to predict how subjective annotators perceive the concreteness of argumentative utterances in urban planning processes. It has been trained to recognize 4 classes: subjective (LABEL_3), rather subjective ... | [
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translation | peft |
# Model Card for Model ID
## Model Details
### Model Description
- **Developed by:** [Kang Seok Ju]
- **Contact:** [brildev7@gmail.com]
## Training Details
### Training Data
https://huggingface.co/datasets/traintogpb/aihub-koen-translation-integrated-tiny-100k
# Inference Examples
```
import os
import torch
from tra... | {"language": ["en", "ko"], "library_name": "peft", "tags": ["translation", "gemma"], "base_model": "google/gemma-7b"} | brildev7/gemma-7b-translation-enko-sft-qlora | null | [
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"en",
"ko"
] | TAGS
#peft #safetensors #translation #gemma #en #ko #base_model-google/gemma-7b #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by: [Kang Seok Ju]
- Contact: [brildev7@URL]
## Training Details
### Training Data
URL
# Inference Examples
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question-answering | transformers |
# Model Card for starman76/t5_500
## Model Details
This model is a fine-tuned version of the T5-small model specifically tailored for question answering tasks in the biomedical domain. It has been trained to understand and generate responses based on biomedical literature, making it particularly useful for researche... | {"library_name": "transformers", "tags": ["transformers", "T5", "question-answering"]} | starman76/t5_500 | null | [
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"text2text-generation",
"T5",
"question-answering",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-11T13:31:52+00:00 | [] | [] | TAGS
#transformers #safetensors #t5 #text2text-generation #T5 #question-answering #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for starman76/t5_500
## Model Details
This model is a fine-tuned version of the T5-small model specifically tailored for question answering tasks in the biomedical domain. It has been trained to understand and generate responses based on biomedical literature, making it particularly useful for researche... | [
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translation | 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. -->
# marian-finetuned-kde4-en-to-fr
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsink... | {"license": "apache-2.0", "tags": ["translation", "generated_from_trainer"], "datasets": ["kde4"], "metrics": ["bleu"], "base_model": "Helsinki-NLP/opus-mt-en-fr", "model-index": [{"name": "marian-finetuned-kde4-en-to-fr", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Mode... | Tsanami/marian-finetuned-kde4-en-to-fr | null | [
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|
# marian-finetuned-kde4-en-to-fr
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-fr on the kde4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8523
- Bleu: 22.3967
## Model description
More information needed
## Intended uses & limitations
More information needed
## T... | [
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"## Model description\n\nMore information needed",
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text-classification | transformers | ## Model Description
**bert-base-german-cased_cimt-argument-subjectivity-2** is a fine-tuned BERT model that is built to predict how subjective annotators perceive the concreteness of argumentative utterances in urban planning processes. It has been trained to recognize 2 classes: rather subjective (LABEL_1) and rathe... | {"language": ["de"], "license": "cc-by-nc-sa-4.0", "tags": ["public participation", "text classification", "argument quality", "subjectivity"]} | juliaromberg/bert-base-german-cased_cimt-argument-subjectivity-2 | null | [
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"region:us"
] | null | 2024-04-11T13:32:45+00:00 | [] | [
"de"
] | TAGS
#transformers #safetensors #bert #text-classification #public participation #text classification #argument quality #subjectivity #de #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
| ## Model Description
bert-base-german-cased_cimt-argument-subjectivity-2 is a fine-tuned BERT model that is built to predict how subjective annotators perceive the concreteness of argumentative utterances in urban planning processes. It has been trained to recognize 2 classes: rather subjective (LABEL_1) and rather ob... | [
"## Model Description\n\nbert-base-german-cased_cimt-argument-subjectivity-2 is a fine-tuned BERT model that is built to predict how subjective annotators perceive the concreteness of argumentative utterances in urban planning processes. It has been trained to recognize 2 classes: rather subjective (LABEL_1) and ra... | [
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null | adapter-transformers |
# Adapter `BigTMiami/adapter_classifier_from_prtrained_test` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head for classification... | {"tags": ["adapter-transformers", "roberta"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/adapter_classifier_from_prtrained_test | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_helpfulness",
"region:us"
] | null | 2024-04-11T13:33:35+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/adapter_classifier_from_prtrained_test' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usage
First, install... | [
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