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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [cognitivecomputations/dolphin-2.8-mistral-7... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["cognitivecomputations/dolphin-2.8-mistral-7b-v02", "arcee-ai/sec-mistral-7b-instruct-1.6-epoch"]} | mergekit-community/mergekit-slerp-hsdezod | null | [
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"text-generation-inference... | null | 2024-04-15T18:12:18+00:00 | [] | [] | TAGS
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| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* cognitivecomputations/dolphin-2.8-mistral-7b-v02
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null | peft | ### Model Description
Utilizacion para crear chatbots de asistencia terapeutica, para poder tener conversaciones en una situacion de necesidad
- **Developed by:** Julio Fullaondo Canga
- **Language(s) (NLP):** Español
- **Finetuned from model [optional]:** gemma-2b-it
- PEFT 0.10.0 | {"library_name": "peft", "base_model": "google/gemma-2b-it"} | Juliofc/chaterapi_model | null | [
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#peft #safetensors #base_model-google/gemma-2b-it #region-us
| ### Model Description
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- Developed by: Julio Fullaondo Canga
- Language(s) (NLP): Español
- Finetuned from model [optional]: gemma-2b-it
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_splice_reconstructed-seqsight_4096_512_27M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_4096_512_27M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_4096_512_27M-L32_all | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_splice\_reconstructed-seqsight\_4096\_512\_27M-L32\_all
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
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null | transformers |
# Model Card for Model ID
This model is created based on the instructions provided in https://www.datacamp.com/tutorial/fine-tuning-google-gemma. It is a PEFT adapter on Gemma-7B fine tuned on a character dataset dialogue.
## Model Details
### Model Description
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# Model Card for Model ID
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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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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_0-seqsight_4096_512_27M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_0-seqsight_4096_512_27M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_4096_512_27M-L32_all | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_0-seqsight\_4096\_512\_27M-L32\_all
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
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* Loss: 0.5407
* F1 Score: 0.7387
* Accurac... | [
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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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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# V0415MA2
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "V0415MA2", "results": []}]} | Litzy619/V0415MA2 | null | [
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| V0415MA2
========
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0650
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
... | [
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null | null |
## WizardLM-2-8x22B-GGUF Quants
Readme to be updated as addtional quants are uploaded.
Q4_K - ~80GB
| {"license": "apache-2.0"} | praxeswolf0d/WizardLM-2-8x22B-GGUF | null | [
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## WizardLM-2-8x22B-GGUF Quants
Readme to be updated as addtional quants are uploaded.
Q4_K - ~80GB
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Reihaneh/wav2vec2_germanic_common_voice_8 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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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. -->
# ryan04152024_ALLDATA
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit... | {"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "ryan04152024_ALLDATA", "results": []}]} | rshrott/ryan04152024_ALLDATA | null | [
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|
# ryan04152024_ALLDATA
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the properties dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1193
- Ordinal Mae: 0.3505
- Ordinal Accuracy: 0.7757
- Na Accuracy: 0.9411
## Model description
More information needed
## ... | [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | mllm-dev/gpt2_untrained | null | [
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# Model Card for Model ID
## Model Details
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token-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | adhi29/model_robertabase_1024_token_classification | null | [
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["cognitivecomputations/dolphin-2.8-mistral-7b-v02", "mistralai/Mistral-7B-v0.1", "microsoft/WizardLM-2-7B", "Nexusflow/Starling-LM-7B-beta"]} | Kukedlc/NeuralSoTa-7b-v0.1 | null | [
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This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the Model Stock merge method using mistralai/Mistral-7B-v0.1 as a base.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Resi/donut-docvqa-sagemaker | 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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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_1-seqsight_4096_512_27M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_1-seqsight_4096_512_27M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_4096_512_27M-L32_all | null | [
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| GUE\_tf\_1-seqsight\_4096\_512\_27M-L32\_all
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | HenryCai1129/LlamaAdapter-llama2-happy-100-lora | null | [
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text-classification | transformers |
# Cross-Encoder for Sentence Similarity
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.
## Training Data
This model was trained on 6 different nli datasets. The model will predict a score between 0 (no... | {"language": ["en", "nl", "de", "fr", "it", "es"], "license": "apache-2.0", "tags": ["feature-extraction", "sentence-similarity", "transformers"], "datasets": ["multi_nli", "pietrolesci/nli_fever"], "pipeline_tag": "text-classification"} | abbasgolestani/ag-nli-DeTS-sentence-similarity-v3-light | null | [
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|
# Cross-Encoder for Sentence Similarity
This model was trained using SentenceTransformers Cross-Encoder class.
## Training Data
This model was trained on 6 different nli datasets. The model will predict a score between 0 (not similar) and 1 (very similar) for the semantic similarity of two sentences.
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"TAGS\n#transformers #pytorch #electra #text-classification #feature-extraction #sentence-similarity #en #nl #de #fr #it #es #dataset-multi_nli #dataset-pietrolesci/nli_fever #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# Cross-Encoder for Sentence Similarity\nThis model was trained ... |
text-generation | transformers |
for test unsloth finetune process and Inference API
**this model overfit with train data so it cannot answer anything not in han dataset**
## prompt
```
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
### I... | {"language": ["th"], "datasets": ["pythainlp/han-instruct-dataset-v2.0"], "base_model": "unsloth/gemma-2b", "pipeline_tag": "text-generation", "widget": [{"text": "\u0e08\u0e07\u0e41\u0e15\u0e48\u0e07\u0e1a\u0e17\u0e01\u0e27\u0e35\u0e40\u0e01\u0e35\u0e48\u0e22\u0e27\u0e01\u0e31\u0e1a\u0e2a\u0e32\u0e22\u0e1d\u0e19\u0e17... | ping98k/gemma-han-2b | null | [
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"th"
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|
for test unsloth finetune process and Inference API
this model overfit with train data so it cannot answer anything not in han dataset
## prompt
| [
"## prompt"
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"TAGS\n#transformers #safetensors #gguf #gemma #text-generation #conversational #th #dataset-pythainlp/han-instruct-dataset-v2.0 #base_model-unsloth/gemma-2b #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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] |
null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Aviral2412/fineturning2 | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-15T18:32:12+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers |
<p style="font-size:20px;" align="center">
🏠 <a href="https://wizardlm.github.io/WizardLM2" target="_blank">WizardLM-2 Release Blog</a> </p>
<p align="center">
🤗 <a href="https://huggingface.co/collections/microsoft/wizardlm-2-661d403f71e6c8257dbd598a" target="_blank">HF Repo</a> •🐱 <a href="https://github.com/... | {"license": "apache-2.0"} | jncraton/WizardLM-2-7B-ct2-int8 | null | [
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"2304.12244",
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#transformers #arxiv-2304.12244 #arxiv-2306.08568 #arxiv-2308.09583 #license-apache-2.0 #endpoints_compatible #region-us
|
<p style="font-size:20px;" align="center">
<a href="URL target="_blank">WizardLM-2 Release Blog</a> </p>
<p align="center">
<a href="URL target="_blank">HF Repo</a> • <a href="URL target="_blank">Github Repo</a> • <a href="URL target="_blank">Twitter</a> • <a href="URL target="_blank">[WizardLM]</a> • <a hr... | [
"## News [2024/04/15]\n\nWe introduce and opensource WizardLM-2, our next generation state-of-the-art large language models, \nwhich have improved performance on complex chat, multilingual, reasoning and agent. \nNew family includes three cutting-edge models: WizardLM-2 8x22B, WizardLM-2 70B, and WizardLM-2 7B.\n\... | [
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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. -->
# wav2vec2-mms-300m-ikk-2
This model is a fine-tuned version of [facebook/mms-300m](https://huggingface.co/facebook/mms-300m) on t... | {"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["wer"], "base_model": "facebook/mms-300m", "model-index": [{"name": "wav2vec2-mms-300m-ikk-2", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name... | ogbi/wav2vec2-mms-300m-ikk-2 | null | [
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"license:cc-by-nc-4.0",
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| wav2vec2-mms-300m-ikk-2
=======================
This model is a fine-tuned version of facebook/mms-300m on the audiofolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3401
* Wer: 0.6359
Model description
-----------------
More information needed
Intended uses & limitations
----... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_4-seqsight_4096_512_27M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_4-seqsight_4096_512_27M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_4096_512_27M-L32_all | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_4-seqsight\_4096\_512\_27M-L32\_all
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3329
* F1 Score: 0.6923
* Accurac... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_3-seqsight_4096_512_27M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_3-seqsight_4096_512_27M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_4096_512_27M-L32_all | null | [
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"generated_from_trainer",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_3-seqsight\_4096\_512\_27M-L32\_all
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6934
* F1 Score: 0.6100
* Accurac... | [
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text2text-generation | transformers | Bio-REBEL
| {"license": "apache-2.0"} | IvyW/rebel_for_bio | null | [
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text-to-image | diffusers | # armor-samurai
<Gallery />
## Model description
Creates renders of Samurai armor by adhicipta
## Trigger words
You should use `samurai` to trigger the image generation.
You should use `armor` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Down... | {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "UNICODE\u0000\u00001\u0000w\u0000o\u0000m\u0000a\u0000n\u0000,\u0000 \u0000p\u0000o\u0000r\u0000t\u0000r\u0000a\u0000i\u0000t\u0000,\u0000 \u0000 \u0000a\u0000 \u0000b\u0000e\u0000a\u0000u\u0000t\u0000i\u0000f\... | MarkBW/armor-samurai | null | [
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"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:runwayml/stable-diffusion-v1-5",
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] | null | 2024-04-15T18:42:38+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-runwayml/stable-diffusion-v1-5 #region-us
| # armor-samurai
<Gallery />
## Model description
Creates renders of Samurai armor by adhicipta
## Trigger words
You should use 'samurai' to trigger the image generation.
You should use 'armor' to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
Downl... | [
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image-classification | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metrics
loss: 0.4315283000469208
f1_macro: 0.6149830093941424
f1_micro: 0.8602430555555556
f1_weighted: 0.8515059109185544
precision_macro: 0.7610988679415244
precision_micro: 0.8602430555555556
precision_weighted: 0.85324448568... | {"tags": ["autotrain", "image-classification"], "datasets": ["xblock-large-patch2-224/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "ex... | howdyaendra/xblock-large-patch2-224 | null | [
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|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metrics
loss: 0.4315283000469208
f1_macro: 0.6149830093941424
f1_micro: 0.8602430555555556
f1_weighted: 0.8515059109185544
precision_macro: 0.7610988679415244
precision_micro: 0.8602430555555556
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="djlouie/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional att... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | djlouie/q-FrozenLake-v1-4x4-noSlippery | null | [
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"reinforcement-learning",
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#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
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] |
null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | HenryCai1129/LlamaAdapter-llama2-happy-300-new | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-15T18:47:50+00:00 | [
"1910.09700"
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_2-seqsight_4096_512_27M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_tf_2-seqsight_4096_512_27M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_4096_512_27M-L32_all | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_tf\_2-seqsight\_4096\_512\_27M-L32\_all
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6898
* F1 Score: 0.7169
* Accurac... | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "meta-llama/Llama-2-7b-chat-hf"} | ASaska/Llama-2-7b-chat-hf | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
#... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | thusinh1969/LLaMA-2-finetune-50k-ep1.42-DPO | null | [
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"1910.09700"
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="djlouie/q-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/... | djlouie/q-Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
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#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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] |
text-generation | transformers |
# ECE-TW3-JRGL-VHF1
ECE-TW3-JRGL-VHF1 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [MTSAIR/MultiVerse_70B](https://huggingface.co/MTSAIR/MultiVerse_70B)
* [davidkim205/Rhea-72b-v0.5](https://huggingface.co/davidkim205/Rhea-72b-v0.5)
## 🧩 Configuration | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "MTSAIR/MultiVerse_70B", "davidkim205/Rhea-72b-v0.5"]} | IAFrance/ECE-TW3-JRGL-VHF1 | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-15T18:54:05+00:00 | [] | [] | TAGS
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|
# ECE-TW3-JRGL-VHF1
ECE-TW3-JRGL-VHF1 is a merge of the following models using mergekit:
* MTSAIR/MultiVerse_70B
* davidkim205/Rhea-72b-v0.5
## Configuration | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | eulpicard/ppo-LunarLander-v2 | null | [
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"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
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#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tomaszki/stablelm-35 | null | [
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"safetensors",
"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-15T18:58:32+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers | # [MaziyarPanahi/WizardLM-2-8x22B-GGUF](https://huggingface.co/MaziyarPanahi/WizardLM-2-8x22B-GGUF)
- Model creator: [microsoft](https://huggingface.co/microsoft)
- Original model: [microsoft/WizardLM-2-8x22B](https://huggingface.co/microsoft/WizardLM-2-8x22B)
## Description
[MaziyarPanahi/WizardLM-2-8x22B-GGUF](https... | {"tags": ["quantized", "2-bit", "3-bit", "4-bit", "5-bit", "6-bit", "8-bit", "GGUF", "transformers", "safetensors", "mistral", "text-generation", "arxiv:2304.12244", "arxiv:2306.08568", "arxiv:2308.09583", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "text-generation-inference", "region:us", "t... | MaziyarPanahi/WizardLM-2-8x22B-GGUF | null | [
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"autotrain_compatible",
"endpoints_compatible",
"tex... | null | 2024-04-15T18:58:51+00:00 | [
"2304.12244",
"2306.08568",
"2308.09583"
] | [] | TAGS
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| # MaziyarPanahi/WizardLM-2-8x22B-GGUF
- Model creator: microsoft
- Original model: microsoft/WizardLM-2-8x22B
## Description
MaziyarPanahi/WizardLM-2-8x22B-GGUF contains GGUF format model files for microsoft/WizardLM-2-8x22B.
## How to download
You can download only the quants you need instead of cloning the entire r... | [
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [NousResearch/Hermes-2-Pro-Mistral-7B](https... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["NousResearch/Hermes-2-Pro-Mistral-7B", "WizardLM/WizardMath-7B-V1.1"]} | mergekit-community/mergekit-slerp-werhsur | null | [
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"mistral",
"text-generation",
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"base_model:WizardLM/WizardMath-7B-V1.1",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-15T18:59:21+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #conversational #base_model-NousResearch/Hermes-2-Pro-Mistral-7B #base_model-WizardLM/WizardMath-7B-V1.1 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* NousResearch/Hermes-2-Pro-Mistral-7B
* WizardLM/WizardMath-7B-V1.1
### Configura... | [
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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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null | transformers |
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text2text-generation | peft | ## Telugu LLaMA 7B Base Model for Causal LM(v1.0)
### Overview
Welcome to the release of the Telugu LLaMA 7B base model – a significant step forward in Language Learning Models (LLMs) for Telugu. This model is specifically designed for Causal Language Modeling (LM) tasks and is ready for immediate inference. It can a... | {"language": ["te"], "license": "mit", "library_name": "peft", "datasets": ["uonlp/CulturaX", "ai4bharat/samanantar"], "pipeline_tag": "text2text-generation"} | Prabhas2002/PreTrained_Telugu_Llama7b | null | [
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| ## Telugu LLaMA 7B Base Model for Causal LM(v1.0)
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null | transformers |
# Uploaded model
- **Developed by:** lomashirl
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b-it-bnb-4bit
This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslot... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl"], "base_model": "unsloth/gemma-2b-it-bnb-4bit"} | lomashirl/Gemma-2b-Alpaca-Gujarati | null | [
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text-generation | transformers |
# CalmexperimentOgnoexperiment27multi_verse_model-7B
CalmexperimentOgnoexperiment27multi_verse_model-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [automerger/Ognoexperiment27Multi_verse_model-7B](https://huggingface.co/automerger/Ognoexperi... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"], "base_model": ["automerger/Ognoexperiment27Multi_verse_model-7B"]} | automerger/CalmexperimentOgnoexperiment27multi_verse_model-7B | null | [
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# CalmexperimentOgnoexperiment27multi_verse_model-7B
CalmexperimentOgnoexperiment27multi_verse_model-7B is an automated merge created by Maxime Labonne using the following configuration.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# GUE_prom_prom_300_tata-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_4096_512_46M-L32_all | null | [
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============================================================
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_notata-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_4096_512_46M-L32_all | null | [
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==============================================================
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text-generation | transformers |
# JSL-MedMNX-7B
[<img src="https://repository-images.githubusercontent.com/104670986/2e728700-ace4-11ea-9cfc-f3e060b25ddf">](http://www.johnsnowlabs.com)
JSL-MedMNX-7B is a 7 Billion parameter model developed by [John Snow Labs](https://www.johnsnowlabs.com/).
This model is trained on medical datasets to provide s... | {"language": ["en"], "license": "cc-by-nc-nd-4.0", "library_name": "transformers", "tags": ["reward model", "RLHF", "medical"]} | johnsnowlabs/JSL-MedMNX-7B | null | [
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| JSL-MedMNX-7B
=============
<img src="URL
JSL-MedMNX-7B is a 7 Billion parameter model developed by John Snow Labs.
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text-generation | transformers |
## Exllama v2 Quantizations of wavecoder-ultra-6.7b
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.18">turboderp's ExLlamaV2 v0.0.18</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branch co... | {"license": "other", "library_name": "transformers", "tags": ["code"], "datasets": ["humaneval"], "metrics": ["code_eval"], "license_name": "deepseek", "pipeline_tag": "text-generation", "quantized_by": "bartowski"} | bartowski/wavecoder-ultra-6.7b-exl2 | null | [
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"endpoints_compatible",
"region:us"
] | null | 2024-04-15T19:18:07+00:00 | [] | [] | TAGS
#transformers #code #text-generation #dataset-humaneval #license-other #endpoints_compatible #region-us
| Exllama v2 Quantizations of wavecoder-ultra-6.7b
------------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.18 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
Each branch contains an individual bits per weight, wit... | [] | [
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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. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": []}]} | AAA01101312/xlm-roberta-base-finetuned-panx-de | null | [
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"safetensors",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"base_model:xlm-roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-15T19:18:35+00:00 | [] | [] | TAGS
#transformers #safetensors #xlm-roberta #token-classification #generated_from_trainer #base_model-xlm-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-de
==================================
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1369
* F1: 0.8633
Model description
-----------------
More information needed
Intended uses & l... | [
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text-generation | transformers | This is an ExLlamaV2 quantized model in 4bpw of [mpasila/PIPPA-Named-7B](https://huggingface.co/mpasila/PIPPA-Named-7B) using the default calibration dataset.
# Original Model card:
This is a merge of [mpasila/PIPPA-Named-LoRA-7B](https://huggingface.co/mpasila/PIPPA-Named-LoRA-7B/).
LoRA trained in 4-bit with 8k co... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "sft", "not-for-all-audiences"], "datasets": ["mpasila/PIPPA-ShareGPT-formatted-named", "KaraKaraWitch/PIPPA-ShareGPT-formatted"], "base_model": "unsloth/mistral-7b-v0.2-bnb-4bit"} | mpasila/PIPPA-Named-7B-exl2-4bpw | null | [
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"base_model:unsloth/mistral-7b-v0.2-bnb-4bi... | null | 2024-04-15T19:24:32+00:00 | [] | [
"en"
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# Original Model card:
This is a merge of mpasila/PIPPA-Named-LoRA-7B.
LoRA trained in 4-bit with 8k context using alpindale/Mistral-7B-v0.2-hf as the base model for 1 epoch.
Dataset used is a modified vers... | [
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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. -->
# interpro_bert_2
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the followi... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "interpro_bert_2", "results": []}]} | Dauka-transformers/interpro_bert_2 | null | [
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#transformers #tensorboard #safetensors #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
| interpro\_bert\_2
=================
This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4333
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 256\n* eval\\_batch\\_size: 128\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 8\n* total\\_train\\_batch\\_size: 2048\n* total\\_eval\\_batch\\_size: 1... | [
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text-generation | transformers |
# ECE-TW3-JRGL-VHF2
ECE-TW3-JRGL-VHF2 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [abacusai/Smaug-72B-v0.1](https://huggingface.co/abacusai/Smaug-72B-v0.1)
* [davidkim205/Rhea-72b-v0.5](https://huggingface.co/davidkim205/Rhea-72b-v0.5)
## 🧩 Configuration | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "abacusai/Smaug-72B-v0.1", "davidkim205/Rhea-72b-v0.5"]} | IAFrance/ECE-TW3-JRGL-VHF2 | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-15T19:28:16+00:00 | [] | [] | TAGS
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|
# ECE-TW3-JRGL-VHF2
ECE-TW3-JRGL-VHF2 is a merge of the following models using mergekit:
* abacusai/Smaug-72B-v0.1
* davidkim205/Rhea-72b-v0.5
## Configuration | [
"# ECE-TW3-JRGL-VHF2\n\nECE-TW3-JRGL-VHF2 is a merge of the following models using mergekit:\n* abacusai/Smaug-72B-v0.1\n* davidkim205/Rhea-72b-v0.5",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_all-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_4096_512_46M-L32_all | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_4096\_512\_46M-L32\_all
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation se... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/microsoft/WizardLM-2-8x22B
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/WizardLM-2-8x2... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "base_model": "microsoft/WizardLM-2-8x22B", "quantized_by": "mradermacher"} | mradermacher/WizardLM-2-8x22B-GGUF | null | [
"transformers",
"en",
"base_model:microsoft/WizardLM-2-8x22B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-15T19:30:03+00:00 | [] | [
"en"
] | TAGS
#transformers #en #base_model-microsoft/WizardLM-2-8x22B #license-apache-2.0 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_notata-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_5... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_4096_512_46M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-15T19:36:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_core\_notata-seqsight\_4096\_512\_46M-L32\_all
===============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the eval... | [
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... | [
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text-generation | transformers |
# ECE-TW3-JRGL-VHF3
ECE-TW3-JRGL-VHF3 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [MTSAIR/MultiVerse_70B](https://huggingface.co/MTSAIR/MultiVerse_70B)
* [davidkim205/Rhea-72b-v0.5](https://huggingface.co/davidkim205/Rhea-72b-v0.5)
## 🧩 Configuration | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "MTSAIR/MultiVerse_70B", "davidkim205/Rhea-72b-v0.5"]} | IAFrance/ECE-TW3-JRGL-VHF3 | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-15T19:39:32+00:00 | [] | [] | TAGS
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|
# ECE-TW3-JRGL-VHF3
ECE-TW3-JRGL-VHF3 is a merge of the following models using mergekit:
* MTSAIR/MultiVerse_70B
* davidkim205/Rhea-72b-v0.5
## Configuration | [
"# ECE-TW3-JRGL-VHF3\n\nECE-TW3-JRGL-VHF3 is a merge of the following models using mergekit:\n* MTSAIR/MultiVerse_70B\n* davidkim205/Rhea-72b-v0.5",
"## Configuration"
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# LoRA DreamBooth - shc/us-election-style
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "diffusers", "lora", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers", "lora", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "runwayml/... | shc/us-election-style | null | [
"diffusers",
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"stable-diffusion",
"stable-diffusion-diffusers",
"base_model:runwayml/stable-diffusion-v1-5",
"license:creativeml-openrail-m",
"region:us"
] | null | 2024-04-15T19:39:54+00:00 | [] | [] | TAGS
#diffusers #text-to-image #lora #diffusers-training #stable-diffusion #stable-diffusion-diffusers #base_model-runwayml/stable-diffusion-v1-5 #license-creativeml-openrail-m #region-us
|
# LoRA DreamBooth - shc/us-election-style
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a photo of US president election using DreamBooth. You can find some example images in the following.
!img_0
!img_1
!img_2
!img_3
LoRA for the text encoder was enabled: Fals... | [
"# LoRA DreamBooth - shc/us-election-style\n\nThese are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a photo of US president election using DreamBooth. You can find some example images in the following. \n\n!img_0\n!img_1\n!img_2\n!img_3\n\n\nLoRA for the text encoder was en... | [
"TAGS\n#diffusers #text-to-image #lora #diffusers-training #stable-diffusion #stable-diffusion-diffusers #base_model-runwayml/stable-diffusion-v1-5 #license-creativeml-openrail-m #region-us \n",
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | heyllm234/sc26 | null | [
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"safetensors",
"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | thdangtr/blip_recipe1m_title_v2 | 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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image-to-text | transformers |
A pre trained ViT and GPT2 is fine tuned on flickr8k dataset. | {"language": ["en"], "license": "apache-2.0", "pipeline_tag": "image-to-text"} | arunmadhusudh/Vit-gpt2-flickr8k | null | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | MLIsaac/ppo-LunarLander-v2 | null | [
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"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
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#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - samahadhoud/the_word_octopus_in_arabic__LoRA
<Gallery />
## Model description
These are samaha... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "lora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "text-to-image", "diffusers-training", "diffusers", "lora", "template:sd-lora", "stabl... | samahadhoud/the_word_octopus_in_arabic__LoRA | null | [
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"license:openrail++",
"region:us"
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#diffusers #tensorboard #text-to-image #diffusers-training #lora #template-sd-lora #stable-diffusion-xl #stable-diffusion-xl-diffusers #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - samahadhoud/the_word_octopus_in_arabic__LoRA
<Gallery />
## Model description
These are samahadhoud/the_word_octopus_in_arabic__LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_tata-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_4096_512_46M-L32_all | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_4096\_512\_46M-L32\_all
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluation... | [
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null | keras |
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
| Hyperparameters | Value |
| :-- | :-- |
| na... | {"library_name": "keras"} | anrhi/mobile_v2__fake_image_Xception_detection | null | [
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"region:us"
] | null | 2024-04-15T19:46:24+00:00 | [] | [] | TAGS
#keras #region-us
| Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
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The following h... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ruBert-base-sberquad-0.001-len_3-filtered-negative
This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggin... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "ai-forever/ruBert-base", "model-index": [{"name": "ruBert-base-sberquad-0.001-len_3-filtered-negative", "results": []}]} | Shalazary/ruBert-base-sberquad-0.001-len_3-filtered-negative | null | [
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"generated_from_trainer",
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#peft #tensorboard #safetensors #generated_from_trainer #base_model-ai-forever/ruBert-base #license-apache-2.0 #region-us
|
# ruBert-base-sberquad-0.001-len_3-filtered-negative
This model is a fine-tuned version of ai-forever/ruBert-base on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training proc... | [
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sentence-similarity | sentence-transformers |
# atasoglu/distilbert-base-turkish-cased-nli-stsb-tr
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.
This model was adapted from [dbmdz/distilbert-base-turkish-cased](h... | {"language": ["tr"], "license": "mit", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "datasets": ["nli_tr", "emrecan/stsb-mt-turkish"], "pipeline_tag": "sentence-similarity", "base_model": "dbmdz/distilbert-base-turkish-cased"} | atasoglu/distilbert-base-turkish-cased-nli-stsb-tr | null | [
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"distilbert",
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"base_model:dbmdz/distilbert-base-turkish-cased",
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|
# atasoglu/distilbert-base-turkish-cased-nli-stsb-tr
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.
This model was adapted from dbmdz/distilbert-base-turkish-cased and fine-tuned on these data... | [
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null | null |
# Aryanne/WizardLM-2-7B-Q4_K_M-GGUF
This model was converted to GGUF format from [`microsoft/WizardLM-2-7B`](https://huggingface.co/microsoft/WizardLM-2-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingfac... | {"license": "apache-2.0", "tags": ["llama-cpp", "gguf-my-repo"]} | Aryanne/WizardLM-2-7B-Q4_K_M-GGUF | null | [
"gguf",
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"gguf-my-repo",
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#gguf #llama-cpp #gguf-my-repo #license-apache-2.0 #region-us
|
# Aryanne/WizardLM-2-7B-Q4_K_M-GGUF
This model was converted to GGUF format from 'microsoft/WizardLM-2-7B' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
Note:... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model was trained from scratch on an unknown dataset.
## Model description
More information needed
## Intended u... | {"tags": ["trl", "sft", "generated_from_trainer"], "model-index": [{"name": "results", "results": []}]} | AbinSingh/results | null | [
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|
# results
This model was trained from scratch on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters w... | [
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text-generation | transformers |
## Llamacpp Quantizations of wavecoder-ultra-6.7b
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2675">b2675</a> for quantization.
Original model: https://huggingface.co/microsoft/wavecoder-ultra-6.7b
All quants made using ... | {"license": "other", "library_name": "transformers", "tags": ["code"], "datasets": ["humaneval"], "metrics": ["code_eval"], "license_name": "deepseek", "pipeline_tag": "text-generation", "quantized_by": "bartowski"} | bartowski/wavecoder-ultra-6.7b-GGUF | null | [
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| Llamacpp Quantizations of wavecoder-ultra-6.7b
----------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Action_model
This model is a fine-tuned version of [Raihan004/Action_model](https://huggingface.co/Raihan004/Action_model) on th... | {"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "Raihan004/Action_model", "model-index": [{"name": "Action_model", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {... | Raihan004/Action_model | null | [
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| Action\_model
=============
This model is a fine-tuned version of Raihan004/Action\_model on the action\_class dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6130
* Accuracy: 0.8330
Model description
-----------------
More information needed
Intended uses & limitations
-----------... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["trl", "sft"], "datasets": ["mlabonne/guanaco-llama2-1k"], "pipeline_tag": "text-generation"} | AbinSingh/mistral_7b_guanaco_finetuned | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gemma-7b-hf-platypus-lamini-vxxiii-chat-enhanced
This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "google/gemma-7b", "model-index": [{"name": "gemma-7b-hf-platypus-lamini-vxxiii-chat-enhanced", "results": []}]} | NassimB/gemma-7b-hf-platypus-lamini-vxxiii-chat-enhanced | null | [
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# gemma-7b-hf-platypus-lamini-vxxiii-chat-enhanced
This model is a fine-tuned version of google/gemma-7b on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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null | null | # Mistral based NIDS
This repository contains an implementation of a Network Intrusion Detection System (NIDS) based on the Mistral Large Language Model (LLM). The system is designed to detect and classify network attacks using natural language processing techniques.
## Overview
- **LLM**:
- The NIDS is built us... | {} | caffeinatedcherrychic/mistral-based-NIDS-old | null | [
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#tensorboard #safetensors #region-us
| # Mistral based NIDS
This repository contains an implementation of a Network Intrusion Detection System (NIDS) based on the Mistral Large Language Model (LLM). The system is designed to detect and classify network attacks using natural language processing techniques.
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text-generation | transformers |
# SambaLingo-Arabic-Chat-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
<!-- Provide a quick summary of what the model is/does. -->
SambaLingo-Arabic-Chat-70B is a human aligned chat model trained in Arabic and English. It is trained using direct pre... | {"language": ["ar", "en"], "license": "llama2", "datasets": ["HuggingFaceH4/ultrachat_200k", "HuggingFaceH4/ultrafeedback_binarized", "HuggingFaceH4/cai-conversation-harmless"]} | sambanovasystems/SambaLingo-Arabic-Chat-70B | null | [
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# SambaLingo-Arabic-Chat-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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text-generation | transformers |
# SambaLingo-Hungarian-Chat-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
<!-- Provide a quick summary of what the model is/does. -->
SambaLingo-Hungarian-Chat-70B is a human aligned chat model trained in Hungarian and English. It is trained using d... | {"language": ["hu", "en"], "license": "llama2", "datasets": ["HuggingFaceH4/ultrachat_200k", "HuggingFaceH4/ultrafeedback_binarized", "HuggingFaceH4/cai-conversation-harmless"]} | sambanovasystems/SambaLingo-Hungarian-Chat-70B | null | [
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# SambaLingo-Hungarian-Chat-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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text-generation | transformers |
# SambaLingo-Thai-Chat-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
<!-- Provide a quick summary of what the model is/does. -->
SambaLingo-Thai-Chat-70B is a human aligned chat model trained in Thai and English. It is trained using direct preferenc... | {"language": ["th", "en"], "license": "llama2", "datasets": ["HuggingFaceH4/ultrachat_200k", "HuggingFaceH4/ultrafeedback_binarized", "HuggingFaceH4/cai-conversation-harmless"]} | sambanovasystems/SambaLingo-Thai-Chat-70B | null | [
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# SambaLingo-Thai-Chat-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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text-generation | transformers |
# SambaLingo-Arabic-Base-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
<!-- Provide a quick summary of what the model is/does. -->
SambaLingo-Arabic-Base-70B is a pretrained Bi-lingual Arabic and English model that adapts [Llama-2-70b](https://huggi... | {"language": ["ar", "en"], "license": "llama2", "datasets": ["uonlp/CulturaX"], "metrics": ["chrf", "accuracy", "bleu"]} | sambanovasystems/SambaLingo-Arabic-Base-70B | null | [
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# SambaLingo-Arabic-Base-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
SambaLingo-Arabic-Base-70B is a pretrained Bi-lingual Arabic and English model that adapts Llama-2-70b to Arabic by training on 28 billion tokens from the Arabic split of the Cu... | [
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text-generation | transformers |
# SambaLingo-Hungarian-Base-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
<!-- Provide a quick summary of what the model is/does. -->
SambaLingo-Hungarian-Base-70B is a pretrained Bi-lingual Hungarian and English model that adapts [Llama-2-70b](http... | {"language": ["hu", "en"], "license": "llama2", "datasets": ["uonlp/CulturaX"], "metrics": ["chrf", "accuracy", "bleu"]} | sambanovasystems/SambaLingo-Hungarian-Base-70B | null | [
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# SambaLingo-Hungarian-Base-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
SambaLingo-Hungarian-Base-70B is a pretrained Bi-lingual Hungarian and English model that adapts Llama-2-70b to Hungarian by training on 19 billion tokens from the Hungarian ... | [
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text-generation | transformers |
# SambaLingo-Thai-Base-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
<!-- Provide a quick summary of what the model is/does. -->
SambaLingo-Thai-Base-70B is a pretrained Bi-lingual Thai and English model that adapts [Llama-2-70b](https://huggingface... | {"language": ["th", "en"], "license": "llama2", "datasets": ["uonlp/CulturaX"], "metrics": ["chrf", "accuracy", "bleu"]} | sambanovasystems/SambaLingo-Thai-Base-70B | null | [
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|
# SambaLingo-Thai-Base-70B
<img src="SambaLingo_Logo.png" width="340" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
SambaLingo-Thai-Base-70B is a pretrained Bi-lingual Thai and English model that adapts Llama-2-70b to Thai by training on 26 billion tokens from the Thai split of the Cultura-X da... | [
"# SambaLingo-Thai-Base-70B\n\n<img src=\"SambaLingo_Logo.png\" width=\"340\" style=\"margin-left:'auto' margin-right:'auto' display:'block'\"/>\n\n\nSambaLingo-Thai-Base-70B is a pretrained Bi-lingual Thai and English model that adapts Llama-2-70b to Thai by training on 26 billion tokens from the Thai split of the... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Weblet/phi-1.5-turbo1 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Novin-AI/Rava-3x7B-v0.1
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up ... | {"language": ["en"], "library_name": "transformers", "base_model": "Novin-AI/Rava-3x7B-v0.1", "quantized_by": "mradermacher"} | mradermacher/Rava-3x7B-v0.1-GGUF | null | [
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#transformers #gguf #en #base_model-Novin-AI/Rava-3x7B-v0.1 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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video-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vivit-b-16x2-collected-dataset
This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/go... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vivit-b-16x2-kinetics400", "model-index": [{"name": "vivit-b-16x2-collected-dataset", "results": []}]} | yehiawp4/vivit-b-16x2-collected-dataset | null | [
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| vivit-b-16x2-collected-dataset
==============================
This model is a fine-tuned version of google/vivit-b-16x2-kinetics400 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2578
* Accuracy: 0.9610
Model description
-----------------
More information needed
Inte... | [
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [Kukedlc/Neural-4-QA-7b](https://huggingface... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Kukedlc/Neural-4-QA-7b", "allknowingroger/NeuralCeptrix-7B-slerp"]} | Kukedlc/Neural-4-QA-7b-v0.2 | null | [
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| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* Kukedlc/Neural-4-QA-7b
* allknowingroger/NeuralCeptrix-7B-slerp
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summarization | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-question-answer-summarization
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5... | {"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "base_model": "google-t5/t5-base", "model-index": [{"name": "t5-base-question-answer-summarization", "results": []}]} | JohnDoe70/t5-summarization | null | [
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| t5-base-question-answer-summarization
=====================================
This model is a fine-tuned version of google-t5/t5-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1420
* Rouge1: 87.2659
* Rouge2: 79.1621
* Rougel: 84.0716
* Rougelsum: 84.0332
Model descri... | [
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sentence-similarity | sentence-transformers |
# Yunika/muril-base-sentence-transformer
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 thi... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "datasets": ["embedding-data/QQP_triplets"], "pipeline_tag": "sentence-similarity"} | Yunika/muril-base-sentence-transformer | null | [
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|
# Yunika/muril-base-sentence-transformer
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.
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | ashwinradhe/m2m_fb | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | devbuzz142/cp05-finetune-gpt2-ALL-NNN4-split-13epoch | null | [
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# Model Card for Model ID
## Model Details
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null | adapter-transformers |
# Adapter `BigTMiami/pretrain_tapt_seq_bn_adpater` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness_TAPT_pretraining_dataset](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness_TAPT_pretraining_dataset/) dataset and inclu... | {"tags": ["adapter-transformers", "roberta"], "datasets": ["BigTMiami/amazon_helpfulness_TAPT_pretraining_dataset"]} | BigTMiami/pretrain_tapt_seq_bn_adpater | null | [
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#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness_TAPT_pretraining_dataset #region-us
|
# Adapter 'BigTMiami/pretrain_tapt_seq_bn_adpater' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness_TAPT_pretraining_dataset dataset and includes a prediction head for masked lm.
This adapter was created for usage with the Adapters library.
## Usage
Firs... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_all-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_4096_512_46M-L32_all | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_4096\_512\_46M-L32\_all
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all dataset.
It achieves the following results on the evaluation set:
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_0-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_mouse_0-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_4096_512_46M-L32_all | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_mouse\_0-seqsight\_4096\_512\_46M-L32\_all
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.7752
* F1 Score: 0.6441
... | [
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text-generation | transformers |
# Sappho_V0.0.3
Sappho_V0.0.3 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)
## 🧩 Configuration
```yaml
models:
- model: mistralai... | {"tags": ["merge", "mergekit", "lazymergekit", "HuggingFaceH4/zephyr-7b-beta"], "base_model": ["HuggingFaceH4/zephyr-7b-beta"]} | Jakolo121/Sappho_V0.0.3 | null | [
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|
# Sappho_V0.0.3
Sappho_V0.0.3 is a merge of the following models using LazyMergekit:
* HuggingFaceH4/zephyr-7b-beta
## Configuration
## Usage
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_1-seqsight_4096_512_46M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_mouse_1-seqsight_4096_512_46M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_4096_512_46M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-15T20:31:36+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_mouse\_1-seqsight\_4096\_512\_46M-L32\_all
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4409
* F1 Score: 0.8219
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | BohdanPetryshyn/codellama-7b-openapi-completion-merged | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- License... | [
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text-generation | transformers |
# ECE-TW3-JRGL-VHF6
ECE-TW3-JRGL-VHF6 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [MTSAIR/MultiVerse_70B](https://huggingface.co/MTSAIR/MultiVerse_70B)
* [abacusai/Smaug-72B-v0.1](https://huggingface.co/abacusai/Smaug-72B-v0.1)
## 🧩 Configuration | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "MTSAIR/MultiVerse_70B", "abacusai/Smaug-72B-v0.1"]} | IAFrance/ECE-TW3-JRGL-VHF6 | null | [
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"license:apache-2.0",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-15T20:35:51+00:00 | [] | [] | TAGS
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|
# ECE-TW3-JRGL-VHF6
ECE-TW3-JRGL-VHF6 is a merge of the following models using mergekit:
* MTSAIR/MultiVerse_70B
* abacusai/Smaug-72B-v0.1
## Configuration | [
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"## Configuration"
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | achen2001/Blip2_Lora | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-15T20:36:54+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.
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="dragonflymoss/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add addition... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | dragonflymoss/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
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#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
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] |
text-generation | transformers |
# ECE-TW3-JRGL-VHF4
ECE-TW3-JRGL-VHF4 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [MTSAIR/MultiVerse_70B](https://huggingface.co/MTSAIR/MultiVerse_70B)
* [abacusai/Smaug-72B-v0.1](https://huggingface.co/abacusai/Smaug-72B-v0.1)
## 🧩 Configuration | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "MTSAIR/MultiVerse_70B", "abacusai/Smaug-72B-v0.1"]} | IAFrance/ECE-TW3-JRGL-VHF4 | null | [
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"llama",
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"lazymergekit",
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-15T20:38:35+00:00 | [] | [] | TAGS
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|
# ECE-TW3-JRGL-VHF4
ECE-TW3-JRGL-VHF4 is a merge of the following models using mergekit:
* MTSAIR/MultiVerse_70B
* abacusai/Smaug-72B-v0.1
## Configuration | [
"# ECE-TW3-JRGL-VHF4\n\nECE-TW3-JRGL-VHF4 is a merge of the following models using mergekit:\n* MTSAIR/MultiVerse_70B\n* abacusai/Smaug-72B-v0.1",
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"TAGS\n#transformers #safetensors #llama #text-generation #merge #mergekit #lazymergekit #MTSAIR/MultiVerse_70B #abacusai/Smaug-72B-v0.1 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# ECE-TW3-JRGL-VHF4\n\nECE-TW3-JRGL-VHF4 is a merge of the following models... |
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. -->
# FineTunedModelTest
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
## Model de... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "gpt2", "model-index": [{"name": "FineTunedModelTest", "results": []}]} | Nada81/FineTunedModelTest | null | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-classification",
"generated_from_trainer",
"base_model:gpt2",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-15T20:39:16+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #gpt2 #text-classification #generated_from_trainer #base_model-gpt2 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# FineTunedModelTest
This model is a fine-tuned version of gpt2 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following... | [
"# FineTunedModelTest\n\nThis model is a fine-tuned version of gpt2 on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training ... | [
"TAGS\n#transformers #tensorboard #safetensors #gpt2 #text-classification #generated_from_trainer #base_model-gpt2 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# FineTunedModelTest\n\nThis model is a fine-tuned version of gpt2 on an unknown dataset.",
"## ... | [
56,
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"TAGS\n#transformers #tensorboard #safetensors #gpt2 #text-classification #generated_from_trainer #base_model-gpt2 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# FineTunedModelTest\n\nThis model is a fine-tuned version of gpt2 on an unknown dataset.## Model descri... |
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