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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | unrented5443/uwtr1rw | null | [
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"safetensors",
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"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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text-to-image | diffusers |
# DreamBooth - SidXXD/test4crossattentionmap-mist-mask-0
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks dog using [DreamBooth](https://dreambooth.github.io/).
You can find some example images in the following.
DreamBooth for the text encoder w... | {"license": "creativeml-openrail-m", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "dreambooth"], "base_model": "CompVis/stable-diffusion-v1-4", "instance_prompt": "a photo of sks dog", "inference": true} | SidXXD/test4crossattentionmap-mist-mask-0 | null | [
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|
# DreamBooth - SidXXD/test4crossattentionmap-mist-mask-0
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks dog using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
| [
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image-text-to-text | transformers |
# Cerule - A Tiny Mighty Vision Model
### Based on Google's - <span style="color: #D56c76;">Gemma-2b + SigLIP</span>
```
ββββββββββββββββββββββ βββ ββββββ ββββββββ
βββββββββββββββββββββββββββ ββββββ ββββββββ
βββ ββββββ βββββββββββ ββββββ ββββββ
βββ ββββββ βββββββββββ ββββββ ββββββ... | {"language": ["en"], "license": "gemma", "pipeline_tag": "image-text-to-text"} | Tensoic/Cerule-v0.1 | null | [
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#transformers #safetensors #cerule-gemma #text-generation #image-text-to-text #custom_code #en #license-gemma #autotrain_compatible #region-us
| Cerule - A Tiny Mighty Vision Model
===================================
### Based on Google's - Gemma-2b + SigLIP
We train and release "Cerule", a tiny yet powerful Vision Lanuage Model based on the newly released Google's Gemma-2b and Google's SigLIP.
The training setup was '4xA100's 80GB' and took ~6 hours to p... | [
"### Based on Google's - Gemma-2b + SigLIP\n\n\nWe train and release \"Cerule\", a tiny yet powerful Vision Lanuage Model based on the newly released Google's Gemma-2b and Google's SigLIP.\n\n\nThe training setup was '4xA100's 80GB' and took ~6 hours to pretrain and ~13 hours to finetune. We modify and adapt the tr... | [
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text-classification | transformers |
#This model is designed to identify and classify text into number of categories:
It leverages advanced Natural Language Processing (NLP) techniques, specifically sentiment analysis, to determine the overall attitude or opinion expressed within a piece of text. By combining this with a dedicated dataset focusing on i... | {"tags": ["autotrain", "text-classification"], "widget": [{"text": "Women and men both are making less when you adjust for inflation than when John Kitzhaber was first elected governor."}]} | eligapris/lie-detection-sentiment-analysis | null | [
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#transformers #safetensors #roberta #text-classification #autotrain #autotrain_compatible #endpoints_compatible #region-us
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summarization | transformers | # SITCC-T5-Classifier Model Card
## Model Description
The SITCC-T5-Classifier model is a fine-tuned version of the google/flan-t5-base model. It has been specifically trained to process IT ticket descriptions and extract the request/issue and the software/system that the ticket is about. The model was fine-tuned using... | {"language": ["en"], "license": "mit", "tags": ["text-2-text", "natural-language", "nlp", "classification", "call center", "IT", "summarization", "text-generation"], "widget": [{"content": "The customer is getting the following error when using rSATS:\nERROR: 'Failed to connect'. \nI have tried restarting the applicati... | KameronB/sitcc-t5-classifier | null | [
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| # SITCC-T5-Classifier Model Card
## Model Description
The SITCC-T5-Classifier model is a fine-tuned version of the google/flan-t5-base model. It has been specifically trained to process IT ticket descriptions and extract the request/issue and the software/system that the ticket is about. The model was fine-tuned using... | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **ALE/Pacman-v5**
This is a trained model of a **DQN** agent playing **ALE/Pacman-v5**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
rein... | {"library_name": "stable-baselines3", "tags": ["ALE/Pacman-v5", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ALE/Pacman-v5", "type": "ALE/Pacm... | ledmands/dqn_Pacman-v5_buff15e5 | null | [
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"ALE/Pacman-v5",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T13:31:10+00:00 | [] | [] | TAGS
#stable-baselines3 #ALE/Pacman-v5 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing ALE/Pacman-v5
This is a trained model of a DQN agent playing ALE/Pacman-v5
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with S... | [
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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. -->
# vit-base-patch16-224-dmae-va-U5-42C
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/g... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224", "model-index": [{"name": "vit-base-patch16-224-dmae-va-U5-42C", "results": []}]} | Augusto777/vit-base-patch16-224-dmae-va-U5-42C | null | [
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| vit-base-patch16-224-dmae-va-U5-42C
===================================
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1112
* Accuracy: 0.5667
Model description
-----------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\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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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | unrented5443/jzcs5yk | null | [
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"text-generation",
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# robust_llm_eowyn-ian-imdb-v0
This model is a fine-tuned version of [stanford-crfm/eowyn-gpt2-medium-x777](https://huggingface.co... | {"tags": ["generated_from_trainer"], "base_model": "stanford-crfm/eowyn-gpt2-medium-x777", "model-index": [{"name": "robust_llm_eowyn-ian-imdb-v0", "results": []}]} | AlignmentResearch/robust_llm_eowyn-ian-imdb-v0 | null | [
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"text-classification",
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"base_model:stanford-crfm/eowyn-gpt2-medium-x777",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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|
# robust_llm_eowyn-ian-imdb-v0
This model is a fine-tuned version of stanford-crfm/eowyn-gpt2-medium-x777 on an unknown 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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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
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text-to-image | diffusers |
# DreamBooth - SidXXD/test4crossattentionmap-mist-mask-1
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks dog using [DreamBooth](https://dreambooth.github.io/).
You can find some example images in the following.
DreamBooth for the text encoder w... | {"license": "creativeml-openrail-m", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "dreambooth"], "base_model": "CompVis/stable-diffusion-v1-4", "instance_prompt": "a photo of sks dog", "inference": true} | SidXXD/test4crossattentionmap-mist-mask-1 | null | [
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"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
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#diffusers #tensorboard #safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #dreambooth #base_model-CompVis/stable-diffusion-v1-4 #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# DreamBooth - SidXXD/test4crossattentionmap-mist-mask-1
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks dog using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
| [
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text-generation | transformers |
# Thai-merge7B-test-03
Thai-merge7B-test-03 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 𧩠Configuration
```yaml
models:
- model: scb10x/typhoon-7b
- model: SeaLLMs/SeaLLM-7B-v2
- model: mistralai/Mistral-7B... | {"tags": ["merge", "mergekit", "lazymergekit"]} | Ksgk-fy/Thai-merge7B-test-03 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T13:42:43+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Thai-merge7B-test-03
Thai-merge7B-test-03 is a merge of the following models using LazyMergekit:
## Configuration
## 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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["unsloth", "trl", "sft"]} | HirCoir/Gemma-2b-Finetuned | null | [
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T13:43:20+00:00 | [
"1910.09700"
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#transformers #pytorch #gemma #text-generation #unsloth #trl #sft #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/wenbopan/Faro-Yi-34B-200K
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Faro-Yi-34B-200K-i1-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one... | {"language": ["en"], "license": "mit", "library_name": "transformers", "datasets": ["wenbopan/Fusang-v1", "wenbopan/OpenOrca-zh-20k"], "base_model": "wenbopan/Faro-Yi-34B-200K", "quantized_by": "mradermacher"} | mradermacher/Faro-Yi-34B-200K-GGUF | null | [
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"base_model:wenbopan/Faro-Yi-34B-200K",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T13:43:37+00:00 | [] | [
"en"
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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. ... | [] | [
"TAGS\n#transformers #gguf #en #dataset-wenbopan/Fusang-v1 #dataset-wenbopan/OpenOrca-zh-20k #base_model-wenbopan/Faro-Yi-34B-200K #license-mit #endpoints_compatible #region-us \n"
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] |
null | fairseq |
This is a finetuned mBART model (https://github.com/facebookresearch/fairseq/tree/main/examples/mbart) suitable for Finnish sentence simplification.
The checkpoint is a **fairseq** checkpoint.
The finetuning data can be obtained here: http://urn.fi/urn:nbn:fi:lb-2024011703.
PID on Kielipankki: http://urn.fi/urn:n... | {"language": ["fi"], "library_name": "fairseq", "tags": ["simplification", "mBART"]} | Helsinki-NLP/fin-simple-mBART | null | [
"fairseq",
"simplification",
"mBART",
"fi",
"region:us"
] | null | 2024-04-02T13:43:48+00:00 | [] | [
"fi"
] | TAGS
#fairseq #simplification #mBART #fi #region-us
|
This is a finetuned mBART model (URL suitable for Finnish sentence simplification.
The checkpoint is a fairseq checkpoint.
The finetuning data can be obtained here: URL
PID on Kielipankki: URL | [] | [
"TAGS\n#fairseq #simplification #mBART #fi #region-us \n"
] | [
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"TAGS\n#fairseq #simplification #mBART #fi #region-us \n"
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null | null | ## Model Storage for the [ScrAIbe](https://github.com/JSchmie/ScrAIbe) Framework
This repository serves as the central storage for the [pyannote.audio](https://huggingface.co/pyannote) diarization model, facilitating easier integration and use within the ScrAIbe framework.
A heartfelt thank you goes to [HervΓ© Bredin]... | {"license": "gpl-3.0"} | Jaikinator/ScrAIbe | null | [
"pytorch",
"license:gpl-3.0",
"region:us"
] | null | 2024-04-02T13:44:27+00:00 | [] | [] | TAGS
#pytorch #license-gpl-3.0 #region-us
| ## Model Storage for the ScrAIbe Framework
This repository serves as the central storage for the URL diarization model, facilitating easier integration and use within the ScrAIbe framework.
A heartfelt thank you goes to HervΓ© Bredin for his active and ongoing development of this powerful model. For those interested i... | [
"## Model Storage for the ScrAIbe Framework\n\nThis repository serves as the central storage for the URL diarization model, facilitating easier integration and use within the ScrAIbe framework.\n\nA heartfelt thank you goes to HervΓ© Bredin for his active and ongoing development of this powerful model. For those int... | [
"TAGS\n#pytorch #license-gpl-3.0 #region-us \n",
"## Model Storage for the ScrAIbe Framework\n\nThis repository serves as the central storage for the URL diarization model, facilitating easier integration and use within the ScrAIbe framework.\n\nA heartfelt thank you goes to HervΓ© Bredin for his active and ongoin... | [
19,
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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. -->
# final_testing
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/bart-base", "model-index": [{"name": "final_testing", "results": []}]} | AniketArtani/final_testing | null | [
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"base_model:facebook/bart-base",
"license:apache-2.0",
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"endpoints_compatible",
"region:us"
] | null | 2024-04-02T13:44:32+00:00 | [] | [] | TAGS
#transformers #safetensors #bart #text2text-generation #generated_from_trainer #base_model-facebook/bart-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# final_testing
This model is a fine-tuned version of facebook/bart-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 hyperparameters
The fo... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# robust_llm_arwen-ian-imdb-v0
This model is a fine-tuned version of [stanford-crfm/arwen-gpt2-medium-x21](https://huggingface.co/... | {"tags": ["generated_from_trainer"], "base_model": "stanford-crfm/arwen-gpt2-medium-x21", "model-index": [{"name": "robust_llm_arwen-ian-imdb-v0", "results": []}]} | AlignmentResearch/robust_llm_arwen-ian-imdb-v0 | null | [
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"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T13:45:27+00:00 | [] | [] | TAGS
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|
# robust_llm_arwen-ian-imdb-v0
This model is a fine-tuned version of stanford-crfm/arwen-gpt2-medium-x21 on an unknown 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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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | 0x0uncle0/Uncle7 | null | [
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"text-generation",
"conversational",
"arxiv:1910.09700",
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"endpoints_compatible",
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] | null | 2024-04-02T13:48:35+00:00 | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model 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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | unrented5443/7q9vbdd | null | [
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## Model Details
### Model Description
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/louisbrulenaudet/DevPearl-7B-dare-ties
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not pl... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "deepseek-ai/deepseek-coder-6.7b-instruct", "defog/sqlcoder-7b-2"], "base_model": "louisbrulenaudet/DevPearl-7B-dare-ties", "quantized_by": "mradermacher"} | mradermacher/DevPearl-7B-dare-ties-GGUF | null | [
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"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T13:51:00+00:00 | [] | [
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] | TAGS
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/intro... | {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-Pixelcopter-PLE-v0", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelco... | swritchie/Reinforce-Pixelcopter-PLE-v0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-02T13:52:46+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | lunarsylph/stablecell_v33 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model 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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | guptasaurabh78/ph2-sau-samsum-ft | null | [
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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. -->
# w2v2-base-pretrained_lr5e-5_at0.4_da1
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/face... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "w2v2-base-pretrained_lr5e-5_at0.4_da1", "results": []}]} | MelanieKoe/w2v2-base-pretrained_lr5e-5_at0.4_da1 | null | [
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"region:us"
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#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-base #license-apache-2.0 #endpoints_compatible #region-us
| w2v2-base-pretrained\_lr5e-5\_at0.4\_da1
========================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4372
* Wer: 0.1666
Model description
-----------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
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text-to-image | diffusers | ### My-Pet-Dog-XZG Dreambooth model trained by pqrstu following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: TCR22CS041
Sample pictures of this concept:
![1](https://huggingface.co/pqr... | {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | pqrstu/my-pet-dog-xzg | null | [
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#diffusers #safetensors #NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
| ### My-Pet-Dog-XZG Dreambooth model trained by pqrstu following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: TCR22CS041
Sample pictures of this concept:
!0
!1
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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. -->
# finetuning-emotionsmodel
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "finetuning-emotionsmodel", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "em... | Sidasthana2212/finetuning-emotionsmodel | null | [
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| finetuning-emotionsmodel
========================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2139
* Accuracy: 0.9235
* F1: 0.9236
Model description
-----------------
More information needed
Intended u... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
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audio-to-audio | null | 
Voice models trained using soundbanks / speechbanks from Team17's Worms videogame series.
"w3dRUS" stands for the Russian localization of Worms 3D with its own soundbanks.
Some training mate... | {"language": ["en", "ru"], "datasets": ["RVC_V2"], "pipeline_tag": "audio-to-audio"} | Stinkek/Worms-RVCv2_RMVPE_200epochs | null | [
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#audio-to-audio #en #ru #dataset-RVC_V2 #region-us
| !Icon_Speechtest.png
Voice models trained using soundbanks / speechbanks from Team17's Worms videogame series.
"w3dRUS" stands for the Russian localization of Worms 3D with its own soundbanks.
Some training material may be manually cleaned from SFX and long silences. Worms 3D variant of Whoopsie got the biggest edits,... | [] | [
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question-answering | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Mo... | {"license": "gpl-2.0", "pipeline_tag": "question-answering"} | seenuvasanfoss/fine_tuned_deberta_question_answering | null | [
"transformers",
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"deberta-v2",
"question-answering",
"arxiv:1910.09700",
"license:gpl-2.0",
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#transformers #safetensors #deberta-v2 #question-answering #arxiv-1910.09700 #license-gpl-2.0 #endpoints_compatible #region-us
|
# Model Card for Model ID
This modelcard aims to be a base template for new models. It has been generated using this raw template.
## Model Details
### Model Description
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- Shared by [optional]:
- Model type: Deberta
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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. -->
# scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma
This model is a fine-tuned version of [haryoaw/scenario-TCR_data... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "haryoaw/scenario-TCR_data-cl-cardiff_cl_only2", "model-index": [{"name": "scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma", "results": []}]} | haryoaw/scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma | null | [
"transformers",
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"xlm-roberta",
"text-classification",
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"base_model:haryoaw/scenario-TCR_data-cl-cardiff_cl_only2",
"license:mit",
"autotrain_compatible",
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] | null | 2024-04-02T13:59:14+00:00 | [] | [] | TAGS
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| scenario-NON-KD-PO-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_gamma
===================================================================
This model is a fine-tuned version of haryoaw/scenario-TCR\_data-cl-cardiff\_cl\_only2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.6776
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 11423\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
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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. -->
# scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta
This model is a fine-tuned version of [haryoaw/scenario-TCR_data... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "haryoaw/scenario-TCR_data-cl-cardiff_cl_only2", "model-index": [{"name": "scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta", "results": []}]} | haryoaw/scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta | null | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
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"base_model:haryoaw/scenario-TCR_data-cl-cardiff_cl_only2",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T13:59:16+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-haryoaw/scenario-TCR_data-cl-cardiff_cl_only2 #license-mit #autotrain_compatible #endpoints_compatible #region-us
| scenario-NON-KD-PO-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_delta
===================================================================
This model is a fine-tuned version of haryoaw/scenario-TCR\_data-cl-cardiff\_cl\_only2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.5684
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 11213\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### Tr... | [
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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. -->
# scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha
This model is a fine-tuned version of [haryoaw/scenario-TCR_data... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "haryoaw/scenario-TCR_data-cl-cardiff_cl_only2", "model-index": [{"name": "scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha", "results": []}]} | haryoaw/scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha | null | [
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"xlm-roberta",
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"base_model:haryoaw/scenario-TCR_data-cl-cardiff_cl_only2",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T13:59:21+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-haryoaw/scenario-TCR_data-cl-cardiff_cl_only2 #license-mit #autotrain_compatible #endpoints_compatible #region-us
| scenario-NON-KD-PO-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_alpha
===================================================================
This model is a fine-tuned version of haryoaw/scenario-TCR\_data-cl-cardiff\_cl\_only2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.2297
... | [
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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. -->
# scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_beta
This model is a fine-tuned version of [haryoaw/scenario-TCR_data-... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "haryoaw/scenario-TCR_data-cl-cardiff_cl_only2", "model-index": [{"name": "scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_beta", "results": []}]} | haryoaw/scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_beta | null | [
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| scenario-NON-KD-PO-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_beta
==================================================================
This model is a fine-tuned version of haryoaw/scenario-TCR\_data-cl-cardiff\_cl\_only2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.5580
* ... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | areegtarek/idefics-9b-instruct-3batchesoneepoch | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model 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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | jr303/sc-Mistral-7B | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers | # Model Card for gpt-sw3-6.7b-v2-translator
The `gpt-sw3-6.7b-v2-translator` is a finetuned version of `gpt-sw3-6.7b-v2-instruct` on a carefully selected translation pair dataset that was gathered by AI Sweden.
## Intended usage:
Translate text data from English to Swedish, or Swedish to English.
## How to use:
```... | {"language": ["sv", "da", "no", "en"], "tags": ["translation"], "base_model": "AI-Sweden-Models/gpt-sw3-6.7b-v2-instruct", "pipeline_tag": "text-generation", "inference": {"parameters": {"temperature": 0.7}}} | AI-Sweden-Models/gpt-sw3-6.7b-v2-translator | null | [
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| Model Card for gpt-sw3-6.7b-v2-translator
=========================================
The 'gpt-sw3-6.7b-v2-translator' is a finetuned version of 'gpt-sw3-6.7b-v2-instruct' on a carefully selected translation pair dataset that was gathered by AI Sweden.
Intended usage:
---------------
Translate text data from Englis... | [] | [
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text-generation | transformers | # Neuronx for [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) - Updated Mistral 7B Model on [AWS Inferentia2](https://aws.amazon.com/ec2/instance-types/inf2/) Using AWS Neuron SDK version 2.18~
This model has been exported to the `neuron` format using specific `input_sha... | {"language": ["en"], "license": "apache-2.0", "tags": ["mistral", "inferentia2", "neuron", "neuronx"], "pipeline_tag": "text-generation", "inference": false} | davidshtian/Mistral-7B-Instruct-v0.2-neuron-4x2048-24-cores-2.18 | null | [
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"conversational",
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#transformers #mistral #text-generation #inferentia2 #neuron #neuronx #conversational #en #license-apache-2.0 #autotrain_compatible #text-generation-inference #region-us
| # Neuronx for mistralai/Mistral-7B-Instruct-v0.2 - Updated Mistral 7B Model on AWS Inferentia2 Using AWS Neuron SDK version 2.18~
This model has been exported to the 'neuron' format using specific 'input_shapes' and 'compiler' parameters detailed in the paragraphs below.
Please refer to the 'optimum-neuron' document... | [
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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"]} | TheSuperGroot/ppo-SnowballTarget | null | [
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|
# 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... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shidowake/240402-Swal-MS-7b-CVec-co0.5-mist-inst-v0.1-co0.5-Hermes-2-Pro-co0.5-openchat_3.5 | null | [
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] | null | 2024-04-02T14:04:16+00:00 | [
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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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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. -->
# layoutlm-funsd-tf
This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-ba... | {"license": "mit", "tags": ["generated_from_keras_callback"], "base_model": "microsoft/layoutlm-base-uncased", "model-index": [{"name": "layoutlm-funsd-tf", "results": []}]} | vfbsilva/layoutlm-funsd-tf | null | [
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| layoutlm-funsd-tf
=================
This model is a fine-tuned version of microsoft/layoutlm-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.5754
* Validation Loss: 1.0073
* Train Overall Precision: 0.4858
* Train Overall Recall: 0.5735
* Train Overall F1... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Pranav-JS/idefics-9b-PokemonCards | null | [
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
xxx is a LMM (Large **M**usic Model) designe... | {"license": "apache-2.0"} | l1v6RWdpLP/pe5z8-125m_lvl | null | [
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|
# xxx model card
Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.
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fill-mask | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_eli5_mlm_model
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["eli5_category"], "base_model": "distilroberta-base", "model-index": [{"name": "my_awesome_eli5_mlm_model", "results": []}]} | kaijie-qin/my_awesome_eli5_mlm_model | null | [
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| my\_awesome\_eli5\_mlm\_model
=============================
This model is a fine-tuned version of distilroberta-base on the eli5\_category dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0071
Model description
-----------------
More information needed
Intended uses & limitations
--... | [
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
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# xxx model card
Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Electro98/my_awesome_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilber... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Electro98/my_awesome_model", "results": []}]} | Electro98/my_awesome_model | null | [
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| Electro98/my\_awesome\_model
============================
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.1447
* Validation Loss: 0.1826
* Train F1: 0.1535
* Train Accuracy: 0.2915
* Epoch: 19
... | [
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automatic-speech-recognition | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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This is the model card of a π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | TifinLab/mms-1b-berber | null | [
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
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# xxx model card
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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-test-alex-final
This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/do... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "base_model": "naver-clova-ix/donut-base", "model-index": [{"name": "donut-test-alex-final", "results": []}]} | alexbeta80/donut-test-alex-final | null | [
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|
# donut-test-alex-final
This model is a fine-tuned version of naver-clova-ix/donut-base on the imagefolder dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
xxx is a LMM (Large **M**usic Model) designe... | {"license": "apache-2.0"} | l1v6RWdpLP/pe5z8-125m-rock | null | [
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|
# xxx model card
Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.
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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. -->
# scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta
This model is a fine-tuned version of [xlm-roberta-base](https:/... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta", "results": []}]} | haryoaw/scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta | null | [
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] | null | 2024-04-02T14:09:03+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-xlm-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| scenario-NON-KD-PR-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_delta
===================================================================
This model is a fine-tuned version of xlm-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.4388
* Accuracy: 0.4390
* F1: 0.4380
... | [
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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. -->
# scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma
This model is a fine-tuned version of [xlm-roberta-base](https:/... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma", "results": []}]} | haryoaw/scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma | null | [
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| scenario-NON-KD-PR-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_gamma
===================================================================
This model is a fine-tuned version of xlm-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.4088
* Accuracy: 0.4452
* F1: 0.4432
... | [
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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. -->
# scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_beta
This model is a fine-tuned version of [xlm-roberta-base](https://... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_beta", "results": []}]} | haryoaw/scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_beta | null | [
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| scenario-NON-KD-PR-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_beta
==================================================================
This model is a fine-tuned version of xlm-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.2732
* Accuracy: 0.4498
* F1: 0.4463
... | [
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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. -->
# scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha
This model is a fine-tuned version of [xlm-roberta-base](https:/... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha", "results": []}]} | haryoaw/scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha | null | [
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| scenario-NON-KD-PR-COPY-CDF-CL-D2\_data-cl-cardiff\_cl\_only\_alpha
===================================================================
This model is a fine-tuned version of xlm-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.4350
* Accuracy: 0.4537
* F1: 0.4493
... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Narkantak/mistral-7b-Intent-Classifier-Ashu-v2 | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
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# xxx model card
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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. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "bert-base-cased", "model-index": [{"name": "bert-finetuned-ner", "results": []}]} | xingjiepan/bert-finetuned-ner | null | [
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| bert-finetuned-ner
==================
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0587
* Precision: 0.9301
* Recall: 0.9488
* F1: 0.9394
* Accuracy: 0.9859
Model description
-----------------
More information nee... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Narkantak/mistral-7b-Intent-Classifier-Ashu-v3 | null | [
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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. -->
# w2v2-base-pretrained_lr5e-5_at0.9_da1
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/face... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "w2v2-base-pretrained_lr5e-5_at0.9_da1", "results": []}]} | MelanieKoe/w2v2-base-pretrained_lr5e-5_at0.9_da1 | null | [
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| w2v2-base-pretrained\_lr5e-5\_at0.9\_da1
========================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
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* Loss: 2.5021
* Wer: 0.1820
Model description
-----------------
More information needed
... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | houssemmoslah/mistral_sql_gen_merged | null | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | 0x0uncle0/Uncle9 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# StrangeMerges_54-7B-model_stock
StrangeMerges_54-7B-model_stock is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 𧩠Configuration
```yaml
models:
- model: Gille/StrangerPerciVaaled_Strange-7B-slerp
- model: rwitz... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit"]} | Gille/StrangeMerges_54-7B-model_stock | null | [
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|
# StrangeMerges_54-7B-model_stock
StrangeMerges_54-7B-model_stock is a merge of the following models using LazyMergekit:
## Configuration
## Usage
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text-generation | transformers |
# Occiglot-7B-ES-EN-Instruct
> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
>
**Occiglot-7B-ES-EN-Instruct** is a th... | {"language": ["en", "es"], "license": "apache-2.0", "pipeline_tag": "text-generation"} | mayflowergmbh/occiglot-7b-es-en-instruct-GPTQ | null | [
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"4-bit",
"region:us"
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#transformers #mistral #text-generation #conversational #en #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| !image/png
Occiglot-7B-ES-EN-Instruct
==========================
>
> A polyglot language model for the Occident.
>
>
>
Occiglot-7B-ES-EN-Instruct is a the instruct version of occiglot-7b-es-en, a generative language model with 7B parameters supporting the Spanish and English and trained by the Occiglot Resea... | [
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
xxx is a LMM (Large **M**usic Model) designe... | {"license": "apache-2.0"} | l1v6RWdpLP/pe5z8-1b5_lvl | null | [
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"text-generation-inference",
"region:us"
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"2301.11975",
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|
# xxx model card
Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.
xxx is a LMM (Large Music Model) designed for symbolic music generation. It is trained on multitrack music ... | [
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text-generation | transformers |
# Occiglot-7B-FR-EN-Instruct
> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
>
**Occiglot-7B-FR-EN-Instruct** is a th... | {"language": ["en", "fr"], "license": "apache-2.0", "pipeline_tag": "text-generation"} | mayflowergmbh/occiglot-7b-fr-en-instruct-GPTQ | null | [
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"fr",
"license:apache-2.0",
"autotrain_compatible",
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"4-bit",
"region:us"
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"en",
"fr"
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#transformers #mistral #text-generation #conversational #en #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| !image/png
Occiglot-7B-FR-EN-Instruct
==========================
>
> A polyglot language model for the Occident.
>
>
>
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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"]} | MrPrjnce/ppo-SnowballTarget | null | [
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"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
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#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... | [
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text-generation | transformers |
# Occiglot-7B-EU5-Instruct
> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
>
**Occiglot-7B-EU5-Instruct** is a the in... | {"language": ["en", "es", "de", "fr", "it"], "license": "apache-2.0", "pipeline_tag": "text-generation"} | mayflowergmbh/occiglot-7b-eu5-instruct-GPTQ | null | [
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] | null | 2024-04-02T14:18:52+00:00 | [] | [
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| !image/png
Occiglot-7B-EU5-Instruct
========================
>
> A polyglot language model for the Occident.
>
>
>
Occiglot-7B-EU5-Instruct is a the instruct version of occiglot-7b-eu5, a generative language model with 7B parameters supporting the top-5 EU languages (English, Spanish, French, German, and Ita... | [
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text-generation | transformers |
# Zebrafish-linear-7B
Zebrafish-linear-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [liminerity/M7-7b](https://huggingface.co/liminerity/M7-7b)
* [rwitz/experiment26-truthy-iter-0](https://huggingface.co/rwitz/expe... | {"license": "cc-by-nc-4.0", "tags": ["merge", "mergekit", "lazymergekit"], "base_model": ["liminerity/M7-7b", "rwitz/experiment26-truthy-iter-0"]} | mlabonne/Zebrafish-linear-7B | null | [
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|
# Zebrafish-linear-7B
Zebrafish-linear-7B is a merge of the following models using LazyMergekit:
* liminerity/M7-7b
* rwitz/experiment26-truthy-iter-0
## Configuration
## Usage
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text-generation | transformers |
# Occiglot-7B-it-en-Instruct
> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
>
**Occiglot-7B-EU5-Instruct** is a the ... | {"language": ["en", "it"], "license": "apache-2.0", "pipeline_tag": "text-generation"} | mayflowergmbh/occiglot-7b-it-en-instruct-GPTQ | null | [
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#transformers #mistral #text-generation #conversational #en #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| !image/png
Occiglot-7B-it-en-Instruct
==========================
>
> A polyglot language model for the Occident.
>
>
>
Occiglot-7B-EU5-Instruct is a the instruct version of occiglot-7b-it-en, a generative language model with 7B parameters supporting the top-5 EU languages (English, Spanish, French, German, a... | [
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
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|
# xxx model card
Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | gsstein/model-25-baseline-llama | 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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token-classification | transformers |
## About
Since their beginnings in the 1830s and 1840s, news agencies have played an important role in the national and international news market, aiming to deliver news as fast and as reliable as possible. While we know that newspapers have been using agency content for a long time to produce their stories, the amou... | {"language": ["fr"], "license": "agpl-3.0"} | impresso-project/bert-newsagency-ner-fr | null | [
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| About
-----
Since their beginnings in the 1830s and 1840s, news agencies have played an important role in the national and international news market, aiming to deliver news as fast and as reliable as possible. While we know that newspapers have been using agency content for a long time to produce their stories, the a... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | dmcooller/shawgpt-ft | 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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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"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small Hi - Sanchit Gandhi", "results": [{"task": {"type": "automatic-speech-recognition", "n... | specccccc/whisper-small-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.
It achieves the following results on the evaluation set:
* Loss: 0.4619
* Wer: 32.7097
Model description
-----------------
More information needed
In... | [
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
xxx is a LMM (Large **M**usic Model) designe... | {"license": "apache-2.0"} | l1v6RWdpLP/pe5z8-1b5-jazz | null | [
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|
# xxx model card
Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.
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text-generation | transformers |
<img src="https://cdn-uploads.huggingface.co/production/uploads/6389d3c61e8755d777902366/-_AiKUEsY3x-N7oY52fdE.jpeg" style="border-radius:2%; width: 66%">
# pandafish-7b
pandafish-7b is an instruct model based on a [Model Stock](https://arxiv.org/abs/2403.19522) merge of the following models (via [LazyMergekit](htt... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit"]} | ichigoberry/pandafish-7b | null | [
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| <img src="URL style="border-radius:2%; width: 66%">
pandafish-7b
============
pandafish-7b is an instruct model based on a Model Stock merge of the following models (via LazyMergekit):
Configuration
-------------
Evals
-----
Usage
-----
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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"]} | RitsRits/ppo-SnowballTarget | null | [
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|
# 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
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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... | Nihith27/dqn-SpaceInvadersNoFrameskip-v4 | null | [
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|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
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text-generation | transformers |
# xxx model card
<!-- Provide a quick summary of what the model is/does. -->
**Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.**
xxx is a LMM (Large **M**usic Model) designe... | {"license": "apache-2.0"} | l1v6RWdpLP/pe5z8-1b5-rock | null | [
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|
# xxx model card
Dear reviewers, this is a one of the pretrained/finetuned versions of xxx. You can freely download it by sending an anonymized request respecting the secret condition mentioned in the paper.
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["trl", "sft"]} | llm87/old-llama-ner | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# L-MChat-7b
<div style="text-align:center;width:250px;height:250px;">
<img src="https://cdn.lauche.eu/logo-l-mchat-rs.png" alt="L-MChat-Series-Logo"">
</div>
L-MChat-7b is a merge of the following models:
* [Nexusflow/Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta)
* [FuseAI/FuseChat-... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "Nexusflow/Starling-LM-7B-beta", "FuseAI/FuseChat-7B-VaRM"], "base_model": ["Nexusflow/Starling-LM-7B-beta", "FuseAI/FuseChat-7B-VaRM"], "model-index": [{"name": "L-MChat-7b", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": ... | Artples/L-MChat-7b | null | [
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"mistral",
"text-generation",
"merge",
"mergekit",
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"conversational",
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"base_model:FuseAI/FuseChat-7B-VaRM",
"license:apache-2.0",
"model-index",
"autotrain_... | null | 2024-04-02T14:31:32+00:00 | [] | [] | TAGS
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==========
L-MChat-7b is a merge of the following models:
* Nexusflow/Starling-LM-7B-beta
* FuseAI/FuseChat-7B-VaRM
Configuration
-------------
Usage
-----
License
-------
Apache 2.0 but you cannot use this model to directly compete with OpenAI.
How?
----
Usage of LazyMergekit... | [] | [
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text-generation | transformers |
<img src="https://cdn-uploads.huggingface.co/production/uploads/5fd5e18a90b6dc4633f6d292/LzEf6vvq2qIiys-q7l9Hq.webp" width="550" />
# MaziyarPanahi/Calme-7B-Instruct-v0.9
## Model Description
Calme-7B is a state-of-the-art language model with 7 billion parameters, fine-tuned over high-quality datasets on top of Mis... | {"license": "apache-2.0", "tags": ["generated_from_trainer", "mistral", "7b", "calme"], "inference": false, "model_creator": "MaziyarPanahi", "pipeline_tag": "text-generation", "quantized_by": "MaziyarPanahi", "model-index": [{"name": "Calme-7B-Instruct-v0.9", "results": []}]} | MaziyarPanahi/Calme-7B-Instruct-v0.9 | null | [
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"mistral",
"text-generation",
"generated_from_trainer",
"7b",
"calme",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T14:34:08+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #generated_from_trainer #7b #calme #license-apache-2.0 #autotrain_compatible #text-generation-inference #region-us
|
<img src="URL width="550" />
# MaziyarPanahi/Calme-7B-Instruct-v0.9
## Model Description
Calme-7B is a state-of-the-art language model with 7 billion parameters, fine-tuned over high-quality datasets on top of Mistral-7B. The Calme-7B models excel in generating text that resonates with clarity, calmness, and cohere... | [
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"### How to... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | GhostLX/ts | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T14:34:37+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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. -->
# swinv2-tiny-patch4-window8-256-finetuned-IDRiD-2
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision"], "model-index": [{"name": "swinv2-tiny-patch4-window8-256-finetuned-IDRiD-2", "results": []}]} | SJChaudhuri/swinv2-tiny-patch4-window8-256-finetuned-IDRiD-2 | null | [
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"tensorboard",
"swinv2",
"image-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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#transformers #pytorch #tensorboard #swinv2 #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| swinv2-tiny-patch4-window8-256-finetuned-IDRiD-2
================================================
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9575
* Precision: 0.6190
Model description
----... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-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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null | peft |
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.0`
```yaml
base_model: mistrala... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "datasets": ["danasone/wikipedia_ru"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "Mistral-7B-v0.1-wikipedia_ru_pruned-0.1", "results": []}]} | WlappaAI/Mistral-7B-v0.1-wikipedia_ru_pruned-0.1 | null | [
"peft",
"safetensors",
"mistral",
"generated_from_trainer",
"dataset:danasone/wikipedia_ru",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"4-bit",
"region:us"
] | null | 2024-04-02T14:38:16+00:00 | [] | [] | TAGS
#peft #safetensors #mistral #generated_from_trainer #dataset-danasone/wikipedia_ru #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #4-bit #region-us
| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
Mistral-7B-v0.1-wikipedia\_ru\_pruned-0.1
=========================================
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on modified danasone/wikipedia\_ru dataset.
It achiev... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 11\n* eval\\_batch\\_size: 11\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_step... | [
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sentence-similarity | sentence-transformers |
# ingeol/facets_gpt_77
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 ea... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | ingeol/facets_gpt_77 | null | [
"sentence-transformers",
"safetensors",
"mpnet",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T14:38:39+00:00 | [] | [] | TAGS
#sentence-transformers #safetensors #mpnet #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# ingeol/facets_gpt_77
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:
Then y... | [
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null | null |
# Experiment26T3qm7xp-7B
Experiment26T3qm7xp-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
## 𧩠Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: rwitz/experiment26-truthy-iter-0
- model: nlpguy/T3QM7XP
merge_m... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/Experiment26T3qm7xp-7B | null | [
"merge",
"mergekit",
"lazymergekit",
"automerger",
"license:apache-2.0",
"region:us"
] | null | 2024-04-02T14:41:55+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #license-apache-2.0 #region-us
|
# Experiment26T3qm7xp-7B
Experiment26T3qm7xp-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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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. -->
# opus-mt-en-bkm-Final-80
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ro](https://huggingface.co/Helsinki-NLP/o... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["arrow"], "metrics": ["bleu"], "base_model": "Helsinki-NLP/opus-mt-en-ro", "model-index": [{"name": "opus-mt-en-bkm-Final-80", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"... | kalese/opus-mt-en-bkm-Final-80 | null | [
"transformers",
"tensorboard",
"safetensors",
"marian",
"text2text-generation",
"generated_from_trainer",
"dataset:arrow",
"base_model:Helsinki-NLP/opus-mt-en-ro",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T14:42:43+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #marian #text2text-generation #generated_from_trainer #dataset-arrow #base_model-Helsinki-NLP/opus-mt-en-ro #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| opus-mt-en-bkm-Final-80
=======================
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ro on the arrow dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4265
* Bleu: 10.3853
* Gen Len: 49.8443
Model description
-----------------
More information needed
Intended... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Gauravpadam/starcoder-whoactuallycodes | null | [
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"safetensors",
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"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
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"text-generation-inference",
"4-bit",
"region:us"
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#transformers #safetensors #starcoder2 #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- 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"]} | ridhoalharits/ppo-SnowballTarget | null | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | null | 2024-04-02T14:44:41+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 *... | [
"TAGS\n#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us \n",
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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"]} | Frankhuhu/ppo-Huggy | null | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | null | 2024-04-02T14:44:59+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you te... | [
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* wh... | [
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"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n W... | [
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199
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"TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrot... |
text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | shesan/horosum | null | [
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"endpoints_compatible",
"text-generation-inference",
"region:us"
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"1910.09700"
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#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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text-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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | harikach24/Medical_QA | null | [
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"1910.09700"
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#transformers #safetensors #gpt2 #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/jondurbin/bagel-34b-v0.5
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/bagel-34b-v0.5-i1-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of... | {"language": ["en"], "license": "other", "library_name": "transformers", "datasets": ["ai2_arc", "allenai/ultrafeedback_binarized_cleaned", "argilla/distilabel-intel-orca-dpo-pairs", "jondurbin/airoboros-3.2", "codeparrot/apps", "facebook/belebele", "bluemoon-fandom-1-1-rp-cleaned", "boolq", "camel-ai/biology", "camel-... | mradermacher/bagel-34b-v0.5-GGUF | null | [
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-----
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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571
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null | null |
# New informations came to surface:
Turkish Interior Minister Ali Yerli Kaya confirmed that an immediate investigation has been opened to find out the reasons behind this incident, and that his ministry will announce the details as soon as it obtains results.
## Continue reading here:
it all started with https://ext... | {} | Jerez651/huggnewsx | null | [
"region:us"
] | null | 2024-04-02T14:46:43+00:00 | [] | [] | TAGS
#region-us
|
# New informations came to surface:
Turkish Interior Minister Ali Yerli Kaya confirmed that an immediate investigation has been opened to find out the reasons behind this incident, and that his ministry will announce the details as soon as it obtains results.
## Continue reading here:
it all started with URL/URL
URL... | [
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"TAGS\n#region-us \n",
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"TAGS\n#region-us \n# New informations came to surface:\n\nTurkish Interior Minister Ali Yerli Kaya confirmed that an immediate investigation has been opened to find out the reasons behind this incident, and that his ministry will announce the details as soon as it obtains results.## Continue reading here:\n\nit al... |
text-generation | transformers |
# Thai-merge7B-test-04
Thai-merge7B-test-04 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 𧩠Configuration
```yaml
models:
- model: scb10x/typhoon-7b
- model: SeaLLMs/SeaLLM-7B-v2
- model: mistralai/Mistral-7B... | {"tags": ["merge", "mergekit", "lazymergekit"]} | Ksgk-fy/Thai-merge7B-test-04 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T14:48:41+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Thai-merge7B-test-04
Thai-merge7B-test-04 is a merge of the following models using LazyMergekit:
## Configuration
## Usage
| [
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"## Configur... | [
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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 π€ transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | JFernandoGRE/mistral_7b_augmenteddemocracy_dups_all3_75 | null | [
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"safetensors",
"mistral",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-02T14:49:40+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
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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. -->
# scenario-TCR-XLMV_data-en-cardiff_eng_only_delta
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-en-cardiff_eng_only_delta", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-en-cardiff_eng_only_delta | null | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
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| scenario-TCR-XLMV\_data-en-cardiff\_eng\_only\_delta
====================================================
This model is a fine-tuned version of facebook/xlm-v-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0986
* Accuracy: 0.3333
* F1: 0.1667
Model description
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 11213\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
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