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text-generation | transformers |
# Nous-Hermes-2-Vision - Mistral 7B
![image/png](https://camo.githubusercontent.com/b09dc35a93b4b70748fa4e2f307b011cd3d548369dd926ec9a2d3a51f7b3721e/68747470733a2f2f66696c65732e6f616975736572636f6e74656e742e636f6d2f66696c652d6b4437565358734f5649576472624b3042353662686644363f73653d323032332d31322d30335431372533413334... | {"language": ["en"], "license": "apache-2.0", "tags": ["mistral", "instruct", "finetune", "chatml", "gpt4", "synthetic data", "distillation", "multimodal", "llava"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "Nous-Hermes-2-Vision", "results": []}]} | jeiku/noushermesvisionalphaconfigedit | null | [
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|
# Nous-Hermes-2-Vision - Mistral 7B
!image/png
*In the tapestry of Greek mythology, Hermes reigns as the eloquent Messenger of the Gods, a deity who deftly bridges the realms through the art of communication. It is in homage to this divine mediator that I name this advanced LLM "Hermes," a system crafted to navigat... | [
"# Nous-Hermes-2-Vision - Mistral 7B\n\n\n!image/png\n\n*In the tapestry of Greek mythology, Hermes reigns as the eloquent Messenger of the Gods, a deity who deftly bridges the realms through the art of communication. It is in homage to this divine mediator that I name this advanced LLM \"Hermes,\" a system crafted... | [
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image-classification | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k"], "metrics": ["accuracy"], "pipeline_tag": "image-classification"} | DaiShiResearch/transnext-small-224-1k | null | [
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| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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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_EMP_H3K4me2-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_43M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-16T22:57:32+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_43M-L32\_all
====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7291
* F1... | [
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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:
* [Citaman/command-r-18-layer](https://hugging... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Citaman/command-r-18-layer"]} | Citaman/command-r-17-layer | null | [
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] | null | 2024-04-16T22:58:22+00:00 | [] | [] | TAGS
#transformers #safetensors #cohere #text-generation #mergekit #merge #conversational #base_model-Citaman/command-r-18-layer #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:
* Citaman/command-r-18-layer
### Configuration
The following YAML configuration w... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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### Model Description
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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 generate... | {"library_name": "transformers", "tags": []} | arzans9/hasil | 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_EMP_H3K9ac-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_43M-L32_all | null | [
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"generated_from_trainer",
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"region:us"
] | null | 2024-04-16T23:01:07+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_43M-L32\_all
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1794
* F1 Sc... | [
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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. -->
# ruRoberta-distilled-med-kd_ner
This model is a fine-tuned version of [DimasikKurd/ruRoberta-distilled-med-kd](https://huggingfac... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "DimasikKurd/ruRoberta-distilled-med-kd", "model-index": [{"name": "ruRoberta-distilled-med-kd_ner", "results": []}]} | DimasikKurd/ruRoberta-distilled-med-kd_ner | null | [
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| ruRoberta-distilled-med-kd\_ner
===============================
This model is a fine-tuned version of DimasikKurd/ruRoberta-distilled-med-kd on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7519
* Precision: 0.5167
* Recall: 0.5141
* F1: 0.5154
* Accuracy: 0.8935
Model descr... | [
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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_EMP_H3K4me3-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_32768_512_43M-L32_all | null | [
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"generated_from_trainer",
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"region:us"
] | null | 2024-04-16T23:02:56+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_32768\_512\_43M-L32\_all
====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6802
* F1... | [
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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_EMP_H4-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H4-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_32768_512_43M-L32_all | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H4-seqsight\_32768\_512\_43M-L32\_all
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4422
* F1 Score: 0.7429
... | [
"### 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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image-classification | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k"], "metrics": ["accuracy"], "pipeline_tag": "image-classification"} | DaiShiResearch/transnext-base-224-1k | null | [
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"vision",
"image-classification",
"en",
"dataset:imagenet-1k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T23:02:57+00:00 | [
"2311.17132"
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"en"
] | TAGS
#pytorch #vision #image-classification #en #dataset-imagenet-1k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
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"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
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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": []}]} | darinj2/xlm-roberta-base-finetuned-panx-de | null | [
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"base_model:xlm-roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T23:03:52+00:00 | [] | [] | TAGS
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| 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: 0.1363
* F1: 0.8658
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
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null | null |
# Experiment26Meliodas-7B
Experiment26Meliodas-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [AurelPx/Meliodas-7b-dare](https://huggingface.co/AurelPx/Meliodas-7b-dare)
## 🧩 Configuration
```yaml
models:
- model: yam-peleg/Experiment26-7B... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"], "base_model": ["AurelPx/Meliodas-7b-dare"]} | automerger/Experiment26Meliodas-7B | null | [
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"lazymergekit",
"automerger",
"base_model:AurelPx/Meliodas-7b-dare",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T23:04:00+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #base_model-AurelPx/Meliodas-7b-dare #license-apache-2.0 #region-us
|
# Experiment26Meliodas-7B
Experiment26Meliodas-7B is an automated merge created by Maxime Labonne using the following configuration.
* AurelPx/Meliodas-7b-dare
## Configuration
## Usage
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] |
image-classification | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k"], "metrics": ["accuracy"], "pipeline_tag": "image-classification"} | DaiShiResearch/transnext-micro-224-1k | null | [
"pytorch",
"vision",
"image-classification",
"en",
"dataset:imagenet-1k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T23:04:57+00:00 | [
"2311.17132"
] | [
"en"
] | TAGS
#pytorch #vision #image-classification #en #dataset-imagenet-1k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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text-generation | transformers |
# carotte
#### Description du Modèle
Ce document fournit des instructions sur l'utilisation du llm `carotte-7b`, spécialement conçu pour répondre à des questions en français.
#### Prérequis
Pour utiliser ce modèle, il est nécessaire d'installer la bibliothèque `transformers` de Hugging Face. Si vous ne l'avez pas dé... | {"language": ["fr", "en"], "license": "apache-2.0", "library_name": "transformers", "pipeline_tag": "text-generation"} | lbl/fr.brain.carotte-7B | null | [
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"mistral",
"text-generation",
"conversational",
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"en",
"license:apache-2.0",
"autotrain_compatible",
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"text-generation-inference",
"region:us"
] | null | 2024-04-16T23:07:08+00:00 | [] | [
"fr",
"en"
] | TAGS
#transformers #safetensors #mistral #text-generation #conversational #fr #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# carotte
#### Description du Modèle
Ce document fournit des instructions sur l'utilisation du llm 'carotte-7b', spécialement conçu pour répondre à des questions en français.
#### Prérequis
Pour utiliser ce modèle, il est nécessaire d'installer la bibliothèque 'transformers' de Hugging Face. Si vous ne l'avez pas dé... | [
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image-classification | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k"], "metrics": ["accuracy"], "pipeline_tag": "image-classification"} | DaiShiResearch/transnext-small-384-1k-ft-1k | null | [
"pytorch",
"vision",
"image-classification",
"en",
"dataset:imagenet-1k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T23:07:35+00:00 | [
"2311.17132"
] | [
"en"
] | TAGS
#pytorch #vision #image-classification #en #dataset-imagenet-1k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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text-classification | transformers |
BENCHMARKS: AVG: 62.97 ARC: 60.58 HellaSwag: 76.03 MMLU: 55.8 TruthfulQA: 52.64 Winogrande: 77.83 GSM8K: 55.72
3b variant of MFANNv0.5
fine-tuned on the MFANN dataset which is still a work in progress, and is a chain-of-thought experiment carried out by me and me alone.
![image/png](https://cdn-uploads.huggingf... | {"license": "apache-2.0", "library_name": "transformers", "datasets": ["netcat420/MFANN"], "pipeline_tag": "text-classification"} | netcat420/MFANN3bv0.4 | null | [
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"text-generation",
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"dataset:netcat420/MFANN",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T23:08:19+00:00 | [] | [] | TAGS
#transformers #safetensors #phi #text-generation #text-classification #dataset-netcat420/MFANN #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
BENCHMARKS: AVG: 62.97 ARC: 60.58 HellaSwag: 76.03 MMLU: 55.8 TruthfulQA: 52.64 Winogrande: 77.83 GSM8K: 55.72
3b variant of MFANNv0.5
fine-tuned on the MFANN dataset which is still a work in progress, and is a chain-of-thought experiment carried out by me and me alone.
!image/png
| [] | [
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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": []} | kevin36524/gemma-Code-Instruct-kFinetune-test | null | [
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"text-generation",
"conversational",
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"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T23:08:52+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #gemma #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
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image-classification | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k"], "metrics": ["accuracy"], "pipeline_tag": "image-classification"} | DaiShiResearch/transnext-base-384-1k-ft-1k | null | [
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"vision",
"image-classification",
"en",
"dataset:imagenet-1k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T23:11:28+00:00 | [
"2311.17132"
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"en"
] | TAGS
#pytorch #vision #image-classification #en #dataset-imagenet-1k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
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"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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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. -->
# ruRoberta-distilled_ner_only
This model is a fine-tuned version of [d0rj/ruRoberta-distilled](https://huggingface.co/d0rj/ruRobe... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "d0rj/ruRoberta-distilled", "model-index": [{"name": "ruRoberta-distilled_ner_only", "results": []}]} | DimasikKurd/ruRoberta-distilled_ner_only | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
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] | null | 2024-04-16T23:14:05+00:00 | [] | [] | TAGS
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| ruRoberta-distilled\_ner\_only
==============================
This model is a fine-tuned version of d0rj/ruRoberta-distilled on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8018
* Precision: 0.5404
* Recall: 0.5323
* F1: 0.5363
* Accuracy: 0.8992
Model description
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 100",
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image-classification | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k"], "metrics": ["accuracy"], "pipeline_tag": "image-classification"} | DaiShiResearch/transnext-micro-AAAA-256-1k | null | [
"pytorch",
"vision",
"image-classification",
"en",
"dataset:imagenet-1k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T23:16:54+00:00 | [
"2311.17132"
] | [
"en"
] | TAGS
#pytorch #vision #image-classification #en #dataset-imagenet-1k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n... | [
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text-generation | transformers | # ChaoticVision
This is a highly experimental merge of two Mistral Llava models with the intent of splitting out a mmproj projector file with a more robust captioning capability. I do not know if this model is functional, and will not be testing it as a language model, so use at your own risk.
## Merge Details
### Me... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["jeiku/llavamistral1.6configedit", "jeiku/noushermesvisionalphaconfigedit"]} | ChaoticNeutrals/ChaoticVision | null | [
"transformers",
"safetensors",
"llava_mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:jeiku/llavamistral1.6configedit",
"base_model:jeiku/noushermesvisionalphaconfigedit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T23:21:44+00:00 | [] | [] | TAGS
#transformers #safetensors #llava_mistral #text-generation #mergekit #merge #conversational #base_model-jeiku/llavamistral1.6configedit #base_model-jeiku/noushermesvisionalphaconfigedit #autotrain_compatible #endpoints_compatible #region-us
| # ChaoticVision
This is a highly experimental merge of two Mistral Llava models with the intent of splitting out a mmproj projector file with a more robust captioning capability. I do not know if this model is functional, and will not be testing it as a language model, so use at your own risk.
## Merge Details
### Me... | [
"# ChaoticVision\n\nThis is a highly experimental merge of two Mistral Llava models with the intent of splitting out a mmproj projector file with a more robust captioning capability. I do not know if this model is functional, and will not be testing it as a language model, so use at your own risk.",
"## Merge Det... | [
"TAGS\n#transformers #safetensors #llava_mistral #text-generation #mergekit #merge #conversational #base_model-jeiku/llavamistral1.6configedit #base_model-jeiku/noushermesvisionalphaconfigedit #autotrain_compatible #endpoints_compatible #region-us \n",
"# ChaoticVision\n\nThis is a highly experimental merge of tw... | [
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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. -->
# model_hh_usp1_dpo1
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_usp1_dpo1", "results": []}]} | guoyu-zhang/model_hh_usp1_dpo1 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-16T23:22:46+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_usp1\_dpo1
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3334
* Rewards/chosen: -12.5084
* Rewards/rejected: -14.9821
* Rewards/accuracies: 0.6800
* Rewards/margins: 2.473... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-mental
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-mental", "results": []}]} | rgao/distilbert-base-uncased-finetuned-mental | null | [
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"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T23:23:51+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert/distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-mental
========================================
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9921
* Accuracy: 0.6760
Model description
-----------------
More info... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Train... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/AlekseiPravdin/NSK-128k-7B-slerp
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "Nitral-AI/Nyan-Stunna-7B", "Nitral-AI/Kunocchini-7b-128k-test", "128k"], "base_model": "AlekseiPravdin/NSK-128k-7B-slerp", "quantized_by": "mradermacher"} | mradermacher/NSK-128k-7B-slerp-GGUF | null | [
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"en"
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
text-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. -->
# dapt_plus_tapt_amazon_helpfulness_classification
This model is a fine-tuned version of [BigTMiami/dapt_plus_tapt_helpfulness_bas... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model", "model-index": [{"name": "dapt_plus_tapt_amazon_helpfulness_classification", "results": []}]} | BigTMiami/dapt_plus_tapt_amazon_helpfulness_classification | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T23:28:07+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model #license-mit #autotrain_compatible #endpoints_compatible #region-us
| dapt\_plus\_tapt\_amazon\_helpfulness\_classification
=====================================================
This model is a fine-tuned version of BigTMiami/dapt\_plus\_tapt\_helpfulness\_base\_pretraining\_model on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3889
* Accurac... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio:... | [
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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_EMP_H3-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_32768_512_43M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-16T23:28:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3-seqsight\_32768\_512\_43M-L32\_all
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.5595
* F1 Score: 0.7161
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 1536\n* eval\\_batch\\_size: 1536\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 | 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. -->
# model_shp3_dpo5
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_shp3_dpo5", "results": []}]} | guoyu-zhang/model_shp3_dpo5 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-16T23:28:35+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_shp3\_dpo5
=================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.1787
* Rewards/chosen: -6.1846
* Rewards/rejected: -8.5969
* Rewards/accuracies: 0.6200
* Rewards/margins: 2.4123
* Logps/... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\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. -->
# results
This model is a fine-tuned version of [ybelkada/falcon-7b-sharded-bf16](https://huggingface.co/ybelkada/falcon-7b-sharde... | {"library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "ybelkada/falcon-7b-sharded-bf16", "model-index": [{"name": "results", "results": []}]} | Mariyyah/results | null | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:ybelkada/falcon-7b-sharded-bf16",
"region:us"
] | null | 2024-04-16T23:32:39+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #base_model-ybelkada/falcon-7b-sharded-bf16 #region-us
|
# results
This model is a fine-tuned version of ybelkada/falcon-7b-sharded-bf16 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 hyperparameter... | [
"# results\n\nThis model is a fine-tuned version of ybelkada/falcon-7b-sharded-bf16 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",
... | [
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"## Model description\n\nMore information needed",
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw2.25 | null | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2402.03300",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T23:42:54+00:00 | [
"2402.03300"
] | [] | TAGS
#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
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text-generation | transformers |
# Uploaded model
- **Developed by:** yiruiz
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-2-13b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/m... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft"], "base_model": "unsloth/llama-2-13b-bnb-4bit"} | yiruiz/llama-2-13b-code-16bit-old | null | [
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|
# Uploaded model
- Developed by: yiruiz
- License: apache-2.0
- Finetuned from model : unsloth/llama-2-13b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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null | transformers |
# 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": []} | Rimyy/GemmaFTMathFormatv1 | null | [
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"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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. -->
# dapt_plus_tapt_amazon_helpfulness_classification_v2
This model is a fine-tuned version of [BigTMiami/dapt_plus_tapt_helpfulness_... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model", "model-index": [{"name": "dapt_plus_tapt_amazon_helpfulness_classification_v2", "results": []}]} | BigTMiami/dapt_plus_tapt_amazon_helpfulness_classification_v2 | null | [
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| dapt\_plus\_tapt\_amazon\_helpfulness\_classification\_v2
=========================================================
This model is a fine-tuned version of BigTMiami/dapt\_plus\_tapt\_helpfulness\_base\_pretraining\_model on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3267
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio:... | [
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw2.5 | null | [
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"arxiv:2402.03300",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T23:53:10+00:00 | [
"2402.03300"
] | [] | TAGS
#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
"TAGS\n#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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null | transformers |
# Uploaded model
- **Developed by:** codesagar
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | codesagar/prompt-guard-classification-v12 | null | [
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|
# Uploaded model
- Developed by: codesagar
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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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... | sgreulic/ppo-LunarLander-v2reborn | null | [
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#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/bongchoi/MoMo-70B-V1.1
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/MoMo-70B-V1.1-i1-G... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "base_model": "bongchoi/MoMo-70B-V1.1", "quantized_by": "mradermacher"} | mradermacher/MoMo-70B-V1.1-GGUF | null | [
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#transformers #gguf #en #base_model-bongchoi/MoMo-70B-V1.1 #license-llama2 #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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object-detection | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k", "coco"], "metrics": ["mean_average_precision"], "pipeline_tag": "object-detection"} | DaiShiResearch/dino-4scale-transnext-tiny-coco | null | [
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"object-detection",
"en",
"dataset:imagenet-1k",
"dataset:coco",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T23:54:24+00:00 | [
"2311.17132"
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"en"
] | TAGS
#pytorch #vision #object-detection #en #dataset-imagenet-1k #dataset-coco #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
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"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
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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_EMP_H4ac-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_32768_512_43M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-16T23:56:17+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H4ac-seqsight\_32768\_512\_43M-L32\_all
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0403
* F1 Score: 0... | [
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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. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axo... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "HuggingFaceTB/cosmo-1b", "model-index": [{"name": "qlora-out", "results": []}]} | Lambent/cosmo-1b-qdora-pythontest | null | [
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"generated_from_trainer",
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| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
qlora-out
=========
This model is a fine-tuned version of HuggingFaceTB/cosmo-1b on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2055
Model description
-----... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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null | null | BENCHMARKS: AVG: 62.97 ARC: 60.58 HellaSwag: 76.03 MMLU: 55.8 TruthfulQA: 52.64 Winogrande: 77.83 GSM8K: 55.72
3b variant of MFANNv0.5
fine-tuned on the MFANN dataset which is still a work in progress, and is a chain-of-thought experiment carried out by me and me alone.
![image/png](https://cdn-uploads.huggingface... | {"license": "apache-2.0"} | netcat420/MFANN3bv0.4-GGUF | null | [
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"region:us"
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#gguf #license-apache-2.0 #region-us
| BENCHMARKS: AVG: 62.97 ARC: 60.58 HellaSwag: 76.03 MMLU: 55.8 TruthfulQA: 52.64 Winogrande: 77.83 GSM8K: 55.72
3b variant of MFANNv0.5
fine-tuned on the MFANN dataset which is still a work in progress, and is a chain-of-thought experiment carried out by me and me alone.
!image/png
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- _load_in_8bit: False
- _load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quan... | {"library_name": "peft", "model-index": [{"name": "gembode-2b-base-ultraalpaca", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "ENEM Challenge (No Images)", "type": "eduagarcia/enem_challenge", "split": "train", "args": {"num_few_shot": 3}}, "metrics": [{"type": "acc",... | recogna-nlp/gembode-2b-base-ultraalpaca | null | [
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] | null | 2024-04-16T23:58:44+00:00 | [] | [] | TAGS
#peft #pytorch #gemma #model-index #has_space #region-us
| Training procedure
------------------
The following 'bitsandbytes' quantization config was used during training:
* quant\_method: bitsandbytes
* \_load\_in\_8bit: False
* \_load\_in\_4bit: True
* llm\_int8\_threshold: 6.0
* llm\_int8\_skip\_modules: None
* llm\_int8\_enable\_fp32\_cpu\_offload: False
* llm\_int8\_h... | [
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] |
object-detection | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k", "coco"], "metrics": ["mean_average_precision"], "pipeline_tag": "object-detection"} | DaiShiResearch/dino-5scale-transnext-tiny-coco | null | [
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"dataset:imagenet-1k",
"dataset:coco",
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"2311.17132"
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#pytorch #vision #object-detection #en #dataset-imagenet-1k #dataset-coco #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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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": []} | gubartz/facetsum-f-2048 | null | [
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"longt5",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T23:59:44+00:00 | [
"1910.09700"
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#transformers #safetensors #longt5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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object-detection | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k", "coco"], "metrics": ["mean_average_precision"], "pipeline_tag": "object-detection"} | DaiShiResearch/dino-5scale-transnext-small-coco | null | [
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"vision",
"object-detection",
"en",
"dataset:imagenet-1k",
"dataset:coco",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:01:39+00:00 | [
"2311.17132"
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"en"
] | TAGS
#pytorch #vision #object-detection #en #dataset-imagenet-1k #dataset-coco #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw3 | null | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2402.03300",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"3-bit",
"region:us"
] | null | 2024-04-17T00:03:39+00:00 | [
"2402.03300"
] | [] | TAGS
#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #3-bit #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
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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_EMP_H3K79me3-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M]... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_32768_512_43M-L32_all | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_32768\_512\_43M-L32\_all
=====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0133
*... | [
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text-generation | transformers |
This is a tiny, dummy version of [Jamba](https://huggingface.co/ai21labs/Jamba-v0.1), used for debugging and experimentation over the Jamba architecture.
It has 128M parameters (instead of 52B), **and is initialized with random weights and did not undergo any training.**
| {"license": "apache-2.0"} | ai21labs/Jamba-tiny-random | null | [
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"jamba",
"text-generation",
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#transformers #safetensors #jamba #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
This is a tiny, dummy version of Jamba, used for debugging and experimentation over the Jamba architecture.
It has 128M parameters (instead of 52B), and is initialized with random weights and did not undergo any training.
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object-detection | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k", "coco"], "metrics": ["mean_average_precision"], "pipeline_tag": "object-detection"} | DaiShiResearch/dino-5scale-transnext-base-coco | null | [
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"vision",
"object-detection",
"en",
"dataset:imagenet-1k",
"dataset:coco",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:04:32+00:00 | [
"2311.17132"
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"en"
] | TAGS
#pytorch #vision #object-detection #en #dataset-imagenet-1k #dataset-coco #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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null | adapter-transformers |
# Adapter `BigTMiami/tapt_seq_bn_amazon_helpfulness_classification_adapter_v2` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head ... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/tapt_seq_bn_amazon_helpfulness_classification_adapter_v2 | null | [
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"roberta",
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#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/tapt_seq_bn_amazon_helpfulness_classification_adapter_v2' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usa... | [
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text-generation | transformers |
# WizardLM-2-4x7B-MoE-exl2-3_0bpw
This is a quantized version of [WizardLM-2-4x7B-MoE](https://huggingface.co/Skylaude/WizardLM-2-4x7B-MoE) an experimental MoE model made with [Mergekit](https://github.com/arcee-ai/mergekit). Quantization was done using version 0.0.18 of [ExLlamaV2](https://github.com/turboderp/exlla... | {"license": "apache-2.0", "tags": ["MoE", "merge", "mergekit", "Mistral", "Microsoft/WizardLM-2-7B"]} | Skylaude/WizardLM-2-4x7B-MoE-exl2-3_0bpw | null | [
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"license:apache-2.0",
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"text-generation-inference",
"3-bit",
"region:us"
] | null | 2024-04-17T00:07:56+00:00 | [] | [] | TAGS
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|
# WizardLM-2-4x7B-MoE-exl2-3_0bpw
This is a quantized version of WizardLM-2-4x7B-MoE an experimental MoE model made with Mergekit. Quantization was done using version 0.0.18 of ExLlamaV2.
Please be sure to set experts per token to 4 for the best results! Context length should be the same as Mistral-7B-Instruct-v0.1... | [
"# WizardLM-2-4x7B-MoE-exl2-3_0bpw\n\nThis is a quantized version of WizardLM-2-4x7B-MoE an experimental MoE model made with Mergekit. Quantization was done using version 0.0.18 of ExLlamaV2. \n\nPlease be sure to set experts per token to 4 for the best results! Context length should be the same as Mistral-7B-Instr... | [
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw3.5 | null | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2402.03300",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-17T00:14:20+00:00 | [
"2402.03300"
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#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
"TAGS\n#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give ... | [
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image-segmentation | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k", "ade20k"], "metrics": ["mean_iou"], "pipeline_tag": "image-segmentation"} | DaiShiResearch/mask2former-transnext-tiny-ade | null | [
"pytorch",
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"image-segmentation",
"en",
"dataset:imagenet-1k",
"dataset:ade20k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:15:04+00:00 | [
"2311.17132"
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"en"
] | TAGS
#pytorch #vision #image-segmentation #en #dataset-imagenet-1k #dataset-ade20k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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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. -->
# model_hh_usp2_dpo1
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_usp2_dpo1", "results": []}]} | guoyu-zhang/model_hh_usp2_dpo1 | null | [
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"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-17T00:15:19+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_usp2\_dpo1
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.5291
* Rewards/chosen: -11.2131
* Rewards/rejected: -13.0930
* Rewards/accuracies: 0.6500
* Rewards/margins: 1.879... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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"TAGS\n#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_... |
image-segmentation | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k", "ade20k"], "metrics": ["mean_iou"], "pipeline_tag": "image-segmentation"} | DaiShiResearch/mask2former-transnext-small-ade | null | [
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"image-segmentation",
"en",
"dataset:imagenet-1k",
"dataset:ade20k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:21:17+00:00 | [
"2311.17132"
] | [
"en"
] | TAGS
#pytorch #vision #image-segmentation #en #dataset-imagenet-1k #dataset-ade20k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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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": []} | adediu25/implicit-debertav3-all | null | [
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"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-17T00:21:51+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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null | null | # `StableLM 2 12B Chat GGUF`
**This repository contains GGUF format files for [StableLM 2 12B Chat](https://huggingface.co/stabilityai/stablelm-2-12b-chat). Files were generated with the [b2684](https://github.com/ggerganov/llama.cpp/releases/tag/b2684) `llama.cpp` release.**
## Model Description
`Stable LM 2 12B Ch... | {"language": ["en"], "license": "other", "tags": ["causal-lm"], "datasets": ["HuggingFaceH4/ultrachat_200k", "allenai/ultrafeedback_binarized_cleaned", "meta-math/MetaMathQA", "WizardLM/WizardLM_evol_instruct_V2_196k", "openchat/openchat_sharegpt4_dataset", "LDJnr/Capybara", "Intel/orca_dpo_pairs", "hkust-nlp/deita-10k... | stabilityai/stablelm-2-12b-chat-GGUF | null | [
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"causal-lm",
"en",
"dataset:HuggingFaceH4/ultrachat_200k",
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"dataset:openchat/openchat_sharegpt4_dataset",
"dataset:LDJnr/Capybara",
"dataset:Intel/orca_dpo_... | null | 2024-04-17T00:23:04+00:00 | [
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"2402.17834"
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"en"
] | TAGS
#gguf #causal-lm #en #dataset-HuggingFaceH4/ultrachat_200k #dataset-allenai/ultrafeedback_binarized_cleaned #dataset-meta-math/MetaMathQA #dataset-WizardLM/WizardLM_evol_instruct_V2_196k #dataset-openchat/openchat_sharegpt4_dataset #dataset-LDJnr/Capybara #dataset-Intel/orca_dpo_pairs #dataset-hkust-nlp/deita-10k-... | 'StableLM 2 12B Chat GGUF'
==========================
This repository contains GGUF format files for StableLM 2 12B Chat. Files were generated with the b2684 'URL' release.
Model Description
-----------------
'Stable LM 2 12B Chat' is a 12 billion parameter instruction tuned language model trained on a mix of pub... | [
"### Training Dataset\n\n\nThe dataset is comprised of a mixture of open datasets large-scale datasets available on the HuggingFace Hub as well as an internal safety dataset:\n\n\n1. SFT Datasets\n\n\n* HuggingFaceH4/ultrachat\\_200k\n* meta-math/MetaMathQA\n* WizardLM/WizardLM\\_evol\\_instruct\\_V2\\_196k\n* Open... | [
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image-segmentation | pytorch |
# TransNeXt
Official Model release
for ["TransNeXt: Robust Foveal Visual Perception for Vision Transformers"](https://arxiv.org/pdf/2311.17132.pdf) [CVPR 2024]
.
## Model Details
- **Code:** https://github.com/DaiShiResearch/TransNeXt
- **Paper:** [TransNeXt: Robust Foveal Visual Perception for Vision Transformers](h... | {"language": ["en"], "license": "apache-2.0", "library_name": "pytorch", "tags": ["vision"], "datasets": ["imagenet-1k", "ade20k"], "metrics": ["mean_iou"], "pipeline_tag": "image-segmentation"} | DaiShiResearch/mask2former-transnext-base-ade | null | [
"pytorch",
"vision",
"image-segmentation",
"en",
"dataset:imagenet-1k",
"dataset:ade20k",
"arxiv:2311.17132",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:23:10+00:00 | [
"2311.17132"
] | [
"en"
] | TAGS
#pytorch #vision #image-segmentation #en #dataset-imagenet-1k #dataset-ade20k #arxiv-2311.17132 #license-apache-2.0 #region-us
| TransNeXt
=========
Official Model release
for "TransNeXt: Robust Foveal Visual Perception for Vision Transformers" [CVPR 2024]
.
Model Details
-------------
* Code: URL
* Paper: TransNeXt: Robust Foveal Visual Perception for Vision Transformers
* Author: Dai Shi
* Email: daishiresearch@URL
Methods
-------
##... | [
"#### Pixel-focused attention (Left) & aggregated attention (Right):\n\n\n!pixel-focused\\_attention",
"#### Convolutional GLU (First on the right):\n\n\n!Convolutional GLU\n\n\nResults\n-------",
"#### Image Classification, Detection and Segmentation:\n\n\n!experiment\\_figure",
"#### Attention Visualization... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilroberta-base-finetuned-mental
This model was trained from scratch on the None dataset.
It achieves the following results o... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "distilroberta-base-finetuned-mental", "results": []}]} | rgao/distilroberta-base-finetuned-mental | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-17T00:23:17+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
| distilroberta-base-finetuned-mental
===================================
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1893
* Accuracy: 0.9333
Model description
-----------------
More information needed
Intended uses & limitations
--... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
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null | null | Reuploads of model from https://github.com/wonjune-kang/lvc-vc
Use my (unofficial) pip package for LVC (I'm not affiliated with the authors) (currently only works on short clips).
```
pip install lvc
```
```python
from lvc import LVC, LVCAudio
l = LVC()
l.infer_file(
'orig.wav',
'sample.wav',
'target.wa... | {"language": ["en"], "license": "mit"} | ml-for-speech/lvc-vc | null | [
"en",
"license:mit",
"region:us"
] | null | 2024-04-17T00:25:37+00:00 | [] | [
"en"
] | TAGS
#en #license-mit #region-us
| Reuploads of model from URL
Use my (unofficial) pip package for LVC (I'm not affiliated with the authors) (currently only works on short clips).
## License
MIT | [
"## License\n\nMIT"
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw3.7 | null | [
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"conversational",
"arxiv:2402.03300",
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"endpoints_compatible",
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"region:us"
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"2402.03300"
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#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
"TAGS\n#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #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": []} | adediu25/implicit-distilbert-all | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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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": []} | Jooonhan/mistral_7b_instruct_v0.2_tridge_summarization | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small Dv - ThatOrJohn
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper... | {"language": ["dv"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_13_0"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small Dv - ThatOrJohn", "results": [{"task": {"type": "automatic-speech-recognition", "name"... | ThatOrJohn/whisper-small-dv | null | [
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| Whisper Small Dv - ThatOrJohn
=============================
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1731
* Wer Ortho: 63.3052
* Wer: 13.5950
Model description
-----------------
More information ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\\_with\\_warmup\n* lr\\_schedule... | [
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw4 | null | [
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"conversational",
"arxiv:2402.03300",
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"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-17T00:37:03+00:00 | [
"2402.03300"
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|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
"TAGS\n#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #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": ["trl", "sft"]} | lilyray/falcon_7b_tomi_sileod | null | [
"transformers",
"safetensors",
"trl",
"sft",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-17T00:43:21+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #trl #sft #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
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null | null |
# DavidAU/SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF
This model was converted to GGUF format from [`upstage/SOLAR-10.7B-Instruct-v1.0`](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0) 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 ... | {"language": ["en"], "license": "cc-by-nc-4.0", "tags": ["llama-cpp", "gguf-my-repo"], "datasets": ["c-s-ale/alpaca-gpt4-data", "Open-Orca/OpenOrca", "Intel/orca_dpo_pairs", "allenai/ultrafeedback_binarized_cleaned"], "base_model": ["upstage/SOLAR-10.7B-v1.0"]} | DavidAU/SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF | null | [
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|
# DavidAU/SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF
This model was converted to GGUF format from 'upstage/SOLAR-10.7B-Instruct-v1.0' 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:... | [
"# DavidAU/SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF\nThis model was converted to GGUF format from 'upstage/SOLAR-10.7B-Instruct-v1.0' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
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null | null |
# DavidAU/SOLAR-10.7B-v1.0-Q6_K-GGUF
This model was converted to GGUF format from [`upstage/SOLAR-10.7B-v1.0`](https://huggingface.co/upstage/SOLAR-10.7B-v1.0) 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://hugging... | {"license": "apache-2.0", "tags": ["llama-cpp", "gguf-my-repo"]} | DavidAU/SOLAR-10.7B-v1.0-Q6_K-GGUF | null | [
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"llama-cpp",
"gguf-my-repo",
"license:apache-2.0",
"region:us"
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#gguf #llama-cpp #gguf-my-repo #license-apache-2.0 #region-us
|
# DavidAU/SOLAR-10.7B-v1.0-Q6_K-GGUF
This model was converted to GGUF format from 'upstage/SOLAR-10.7B-v1.0' 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:
Not... | [
"# DavidAU/SOLAR-10.7B-v1.0-Q6_K-GGUF\nThis model was converted to GGUF format from 'upstage/SOLAR-10.7B-v1.0' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
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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. -->
# mistral7binstruct_summarize
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mi... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral7binstruct_summarize", "results": []}]} | asahikuroki222/mistral7binstruct_summarize | null | [
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| mistral7binstruct\_summarize
============================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6534
Model description
-----------------
More information needed
Intended uses & limit... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# clasificador-dair-ai
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ... | {"license": "apache-2.0", "tags": ["classification", "generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "clasificador-dair-ai", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "... | angela1996/clasificador-dair-ai | null | [
"transformers",
"safetensors",
"bert",
"text-classification",
"classification",
"generated_from_trainer",
"dataset:emotion",
"base_model:bert-base-uncased",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-17T00:47:26+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #text-classification #classification #generated_from_trainer #dataset-emotion #base_model-bert-base-uncased #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| clasificador-dair-ai
====================
This model is a fine-tuned version of bert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2186
* Accuracy: 0.928
Model description
-----------------
More information needed
Intended uses & limitations
----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3.0",
"### Traini... | [
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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. -->
# mistral7binstruct_summarize
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mi... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral7binstruct_summarize", "results": []}]} | andre-fichel/mistral7binstruct_summarize | null | [
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"dataset:generator",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:47:58+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
| mistral7binstruct\_summarize
============================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4326
Model description
-----------------
More information needed
Intended uses & limit... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_step... | [
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw4.2 | null | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2402.03300",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-17T00:47:58+00:00 | [
"2402.03300"
] | [] | TAGS
#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
"TAGS\n#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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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 [TIES](https://arxiv.org/abs/2306.01708) merge method using [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["arcee-ai/Patent-Instruct-7b", "microsoft/Orca-2-7b", "NousResearch/Llama-2-7b-hf"]} | mergekit-community/mergekit-ties-zwxzpdk | null | [
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"base_model:NousResearch/Llama-2-7b-hf",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference"... | null | 2024-04-17T00:49:44+00:00 | [
"2306.01708"
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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 TIES merge method using NousResearch/Llama-2-7b-hf as a base.
### Models Merged
The following models were included in the merge:
* arcee-ai/Patent-Instruct-7b
* microsoft... | [
"# merge\n\nThis is a merge of pre-trained language models created using mergekit.",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the TIES merge method using NousResearch/Llama-2-7b-hf as a base.",
"### Models Merged\n\nThe following models were included in the merge:\n* arcee-ai/Paten... | [
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text-generation | transformers | # kululemon-spiked-9B-8.0bpw_h8_exl2
This is a frankenmerge of a pre-trained language model created using [mergekit](https://github.com/cg123/mergekit). As an experiment, this appears to be a partial success.
Lightly tested with temperature 1 and minP 0.01 with ChatML prompts; the model supports Alpaca prompts and ha... | {"license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["grimjim/kukulemon-7B"], "pipeline_tag": "text-generation"} | grimjim/kukulemon-spiked-9B-8.0bpw_h8_exl2 | null | [
"transformers",
"safetensors",
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"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"8-bit",
"region:us"
] | null | 2024-04-17T00:54:56+00:00 | [] | [] | TAGS
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| # kululemon-spiked-9B-8.0bpw_h8_exl2
This is a frankenmerge of a pre-trained language model created using mergekit. As an experiment, this appears to be a partial success.
Lightly tested with temperature 1 and minP 0.01 with ChatML prompts; the model supports Alpaca prompts and has 8K context length, a result of its ... | [
"# kululemon-spiked-9B-8.0bpw_h8_exl2\n\nThis is a frankenmerge of a pre-trained language model created using mergekit. As an experiment, this appears to be a partial success.\n\nLightly tested with temperature 1 and minP 0.01 with ChatML prompts; the model supports Alpaca prompts and has 8K context length, a resul... | [
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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. -->
# model_usp1_dpo5
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_usp1_dpo5", "results": []}]} | guoyu-zhang/model_usp1_dpo5 | null | [
"peft",
"safetensors",
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"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-17T00:55:17+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_usp1\_dpo5
=================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2734
* Rewards/chosen: -2.3548
* Rewards/rejected: -7.1210
* Rewards/accuracies: 0.6900
* Rewards/margins: 4.7662
* Logps/... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\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. -->
# mistral7binstruct_summarize
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mi... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral7binstruct_summarize", "results": []}]} | jkim-aalto/mistral7binstruct_summarize | null | [
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| mistral7binstruct\_summarize
============================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4126
Model description
-----------------
More information needed
Intended uses & limit... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_step... | [
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sentence-similarity | sentence-transformers |
# snowflake-arctic-embed-l-gguf
Model creator: [Snowflake](https://huggingface.co/Snowflake)
Original model: [snowflake-arctic-embed-l](https://huggingface.co/Snowflake/snowflake-arctic-embed-l)
## Original Description
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality... | {"language": ["en"], "license": "apache-2.0", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "mteb", "arctic", "snowflake-arctic-embed", "transformers.js", "gguf"], "model_name": "snowflake-arctic-embed-l", "base_model": "Snowflake/snowflake-arcti... | ChristianAzinn/snowflake-arctic-embed-l-gguf | null | [
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"feature-extraction",
"sentence-similarity",
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"base_model:Snowflake/snowflake-arctic-embed-l",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:56:05+00:00 | [] | [
"en"
] | TAGS
#sentence-transformers #feature-extraction #sentence-similarity #mteb #arctic #snowflake-arctic-embed #transformers.js #gguf #en #base_model-Snowflake/snowflake-arctic-embed-l #license-apache-2.0 #region-us
| snowflake-arctic-embed-l-gguf
=============================
Model creator: Snowflake
Original model: snowflake-arctic-embed-l
Original Description
--------------------
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality retrieval models optimized for performance.
T... | [
"### snowflake-arctic-embed-l\n\n\nBased on the intfloat/e5-large-unsupervised model, this small model does not sacrifice retrieval accuracy for its small size.\n\n\n\nDescription\n-----------\n\n\nThis repo contains GGUF format files for the snowflake-arctic-embed-l embedding model.\n\n\nThese files were converted... | [
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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_EMP_H3K4me1-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_32768_512_43M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-17T00:56:35+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_32768\_512\_43M-L32\_all
====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0239
* F1... | [
"### 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 | 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. -->
# model_shp4_dpo5
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_shp4_dpo5", "results": []}]} | guoyu-zhang/model_shp4_dpo5 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-17T00:56:44+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_shp4\_dpo5
=================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6900
* Rewards/chosen: -4.3601
* Rewards/rejected: -4.8463
* Rewards/accuracies: 0.5100
* Rewards/margins: 0.4862
* Logps/... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradi... | [
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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": []} | relu-ntnu/bart-large-cnn_v2_trained_on_1000 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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"# Model Card for Model ID",
"## Model Details",
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null | null |
# DavidAU/SOLAR-10.7B-Instruct-v1.0-uncensored-Q6_K-GGUF
This model was converted to GGUF format from [`w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored`](https://huggingface.co/w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-rep... | {"license": "apache-2.0", "tags": ["llama-cpp", "gguf-my-repo"]} | DavidAU/SOLAR-10.7B-Instruct-v1.0-uncensored-Q6_K-GGUF | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:57:32+00:00 | [] | [] | TAGS
#gguf #llama-cpp #gguf-my-repo #license-apache-2.0 #region-us
|
# DavidAU/SOLAR-10.7B-Instruct-v1.0-uncensored-Q6_K-GGUF
This model was converted to GGUF format from 'w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored' 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 se... | [
"# DavidAU/SOLAR-10.7B-Instruct-v1.0-uncensored-Q6_K-GGUF\nThis model was converted to GGUF format from 'w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nI... | [
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"# DavidAU/SOLAR-10.7B-Instruct-v1.0-uncensored-Q6_K-GGUF\nThis model was converted to GGUF format from 'w4r10ck/SOLAR-10.7B-Instruct-v1.0-uncensored' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more de... | [
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sentence-similarity | sentence-transformers |
# snowflake-arctic-embed-m-long-gguf
Model creator: [Snowflake](https://huggingface.co/Snowflake)
Original model: [snowflake-arctic-embed-m-long](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-long)
## Original Description
snowflake-arctic-embed is a suite of text embedding models that focuses on creati... | {"language": ["en"], "license": "apache-2.0", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "mteb", "arctic", "snowflake-arctic-embed", "transformers.js", "gguf"], "model_name": "snowflake-arctic-embed-m-long", "base_model": "Snowflake/snowflake-... | ChristianAzinn/snowflake-arctic-embed-m-long-GGUF | null | [
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"mteb",
"arctic",
"snowflake-arctic-embed",
"transformers.js",
"gguf",
"en",
"base_model:Snowflake/snowflake-arctic-embed-m-long",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T00:58:42+00:00 | [] | [
"en"
] | TAGS
#sentence-transformers #feature-extraction #sentence-similarity #mteb #arctic #snowflake-arctic-embed #transformers.js #gguf #en #base_model-Snowflake/snowflake-arctic-embed-m-long #license-apache-2.0 #region-us
| snowflake-arctic-embed-m-long-gguf
==================================
Model creator: Snowflake
Original model: snowflake-arctic-embed-m-long
Original Description
--------------------
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality retrieval models optimized for p... | [
"### snowflake-arctic-embed-m-long\n\n\nBased on the nomic-ai/nomic-embed-text-v1-unsupervised model, this long-context variant of our medium-sized model is perfect for workloads that can be constrained by the regular 512 token context of our other models. Without the use of RPE, this model supports up to 2048 toke... | [
"TAGS\n#sentence-transformers #feature-extraction #sentence-similarity #mteb #arctic #snowflake-arctic-embed #transformers.js #gguf #en #base_model-Snowflake/snowflake-arctic-embed-m-long #license-apache-2.0 #region-us \n",
"### snowflake-arctic-embed-m-long\n\n\nBased on the nomic-ai/nomic-embed-text-v1-unsuperv... | [
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null | transformers |
# DavidAU/UNA-SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF
This model was converted to GGUF format from [`fblgit/UNA-SOLAR-10.7B-Instruct-v1.0`](https://huggingface.co/fblgit/UNA-SOLAR-10.7B-Instruct-v1.0) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the ... | {"language": ["en"], "license": "cc-by-nc-nd-4.0", "library_name": "transformers", "tags": ["alignment-handbook", "generated_from_trainer", "UNA", "single-turn", "llama-cpp", "gguf-my-repo"], "base_model": "upstage/SOLAR-10.7B-Instruct-v1.0", "model-index": [{"name": "UNA-SOLAR-10.7B-Instruct-v1.0", "results": []}]} | DavidAU/UNA-SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF | null | [
"transformers",
"gguf",
"alignment-handbook",
"generated_from_trainer",
"UNA",
"single-turn",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:upstage/SOLAR-10.7B-Instruct-v1.0",
"license:cc-by-nc-nd-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-17T00:58:58+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #alignment-handbook #generated_from_trainer #UNA #single-turn #llama-cpp #gguf-my-repo #en #base_model-upstage/SOLAR-10.7B-Instruct-v1.0 #license-cc-by-nc-nd-4.0 #endpoints_compatible #region-us
|
# DavidAU/UNA-SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF
This model was converted to GGUF format from 'fblgit/UNA-SOLAR-10.7B-Instruct-v1.0' 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... | [
"# DavidAU/UNA-SOLAR-10.7B-Instruct-v1.0-Q6_K-GGUF\nThis model was converted to GGUF format from 'fblgit/UNA-SOLAR-10.7B-Instruct-v1.0' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL s... | [
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw4.4 | null | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2402.03300",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-17T00:59:00+00:00 | [
"2402.03300"
] | [] | TAGS
#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
"TAGS\n#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give ... | [
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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 [automerger/YamshadowExperiment28-7B](https://huggingface.co/automer... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["automerger/YamshadowExperiment28-7B", "CultriX/NeuralTrix-bf16", "CultriX/MonaTrix-v4", "CultriX/MonaCeption-7B-SLERP-DPO"]} | CultriX/ACultriX-7B | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"arxiv:2403.19522",
"base_model:automerger/YamshadowExperiment28-7B",
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"base_model:CultriX/MonaTrix-v4",
"base_model:CultriX/MonaCeption-7B-SLERP-DPO",
"autotrain_compatible",... | null | 2024-04-17T01:00:17+00:00 | [
"2403.19522"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #arxiv-2403.19522 #base_model-automerger/YamshadowExperiment28-7B #base_model-CultriX/NeuralTrix-bf16 #base_model-CultriX/MonaTrix-v4 #base_model-CultriX/MonaCeption-7B-SLERP-DPO #autotrain_compatible #endpoints_compatible #text-generation-infer... | # merge
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 automerger/YamshadowExperiment28-7B as a base.
### Models Merged
The following models were included in the merge:
* CultriX/NeuralTrix-bf16... | [
"# merge\n\nThis is a merge of pre-trained language models created using mergekit.",
"## Merge Details",
"### Merge Method\n\nThis model was merged using the Model Stock merge method using automerger/YamshadowExperiment28-7B as a base.",
"### Models Merged\n\nThe following models were included in the merge:\n... | [
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null | null |
# DavidAU/S-SOLAR-10.7B-v1.5-Q6_K-GGUF
This model was converted to GGUF format from [`hwkwon/S-SOLAR-10.7B-v1.5`](https://huggingface.co/hwkwon/S-SOLAR-10.7B-v1.5) 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://hug... | {"language": ["ko"], "license": "cc-by-nc-4.0", "tags": ["llama-cpp", "gguf-my-repo"]} | DavidAU/S-SOLAR-10.7B-v1.5-Q6_K-GGUF | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"ko",
"license:cc-by-nc-4.0",
"region:us"
] | null | 2024-04-17T01:00:24+00:00 | [] | [
"ko"
] | TAGS
#gguf #llama-cpp #gguf-my-repo #ko #license-cc-by-nc-4.0 #region-us
|
# DavidAU/S-SOLAR-10.7B-v1.5-Q6_K-GGUF
This model was converted to GGUF format from 'hwkwon/S-SOLAR-10.7B-v1.5' 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:
... | [
"# DavidAU/S-SOLAR-10.7B-v1.5-Q6_K-GGUF\nThis model was converted to GGUF format from 'hwkwon/S-SOLAR-10.7B-v1.5' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL server or the CLI.\n\nC... | [
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sentence-similarity | sentence-transformers |
# snowflake-arctic-embed-m-gguf
Model creator: [Snowflake](https://huggingface.co/Snowflake)
Original model: [snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m)
## Original Description
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality... | {"language": ["en"], "license": "apache-2.0", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "mteb", "arctic", "snowflake-arctic-embed", "transformers.js", "gguf"], "model_name": "snowflake-arctic-embed-m", "base_model": "Snowflake/snowflake-arcti... | ChristianAzinn/snowflake-arctic-embed-m-gguf | null | [
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"mteb",
"arctic",
"snowflake-arctic-embed",
"transformers.js",
"gguf",
"en",
"base_model:Snowflake/snowflake-arctic-embed-m",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T01:03:31+00:00 | [] | [
"en"
] | TAGS
#sentence-transformers #feature-extraction #sentence-similarity #mteb #arctic #snowflake-arctic-embed #transformers.js #gguf #en #base_model-Snowflake/snowflake-arctic-embed-m #license-apache-2.0 #region-us
| snowflake-arctic-embed-m-gguf
=============================
Model creator: Snowflake
Original model: snowflake-arctic-embed-m
Original Description
--------------------
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality retrieval models optimized for performance.
T... | [
"### snowflake-arctic-embed-m\n\n\nBased on the intfloat/e5-base-unsupervised model, this medium model is the workhorse that provides the best retrieval performance without slowing down inference.\n\n\n\nDescription\n-----------\n\n\nThis repo contains GGUF format files for the snowflake-arctic-embed-m embedding mo... | [
"TAGS\n#sentence-transformers #feature-extraction #sentence-similarity #mteb #arctic #snowflake-arctic-embed #transformers.js #gguf #en #base_model-Snowflake/snowflake-arctic-embed-m #license-apache-2.0 #region-us \n",
"### snowflake-arctic-embed-m\n\n\nBased on the intfloat/e5-base-unsupervised model, this mediu... | [
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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. -->
# image_classification_for_fracture
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "image_classification_for_fracture", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dat... | akhileshav8/image_classification_for_fracture | null | [
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| image\_classification\_for\_fracture
====================================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4783
* Accuracy: 0.85
Model description
-----------------
More informat... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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sentence-similarity | sentence-transformers |
# snowflake-arctic-embed-s-gguf
Model creator: [Snowflake](https://huggingface.co/Snowflake)
Original model: [snowflake-arctic-embed-s](https://huggingface.co/Snowflake/snowflake-arctic-embed-s)
## Original Description
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality... | {"language": ["en"], "license": "apache-2.0", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "mteb", "arctic", "snowflake-arctic-embed", "transformers.js", "gguf"], "model_name": "snowflake-arctic-embed-s", "base_model": "Snowflake/snowflake-arcti... | ChristianAzinn/snowflake-arctic-embed-s-gguf | null | [
"sentence-transformers",
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"license:apache-2.0",
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| snowflake-arctic-embed-s-gguf
=============================
Model creator: Snowflake
Original model: snowflake-arctic-embed-s
Original Description
--------------------
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality retrieval models optimized for performance.
T... | [] | [
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] |
sentence-similarity | sentence-transformers |
# snowflake-arctic-embed-xs-gguf
Model creator: [Snowflake](https://huggingface.co/Snowflake)
Original model: [snowflake-arctic-embed-xs](https://huggingface.co/Snowflake/snowflake-arctic-embed-xs)
## Original Description
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-qual... | {"language": ["en"], "license": "apache-2.0", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "mteb", "arctic", "snowflake-arctic-embed", "transformers.js", "gguf"], "model_name": "snowflake-arctic-embed-xs", "base_model": "Snowflake/snowflake-arct... | ChristianAzinn/snowflake-arctic-embed-xs-gguf | null | [
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"sentence-similarity",
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"en",
"base_model:Snowflake/snowflake-arctic-embed-xs",
"license:apache-2.0",
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"en"
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| snowflake-arctic-embed-xs-gguf
==============================
Model creator: Snowflake
Original model: snowflake-arctic-embed-xs
Original Description
--------------------
snowflake-arctic-embed is a suite of text embedding models that focuses on creating high-quality retrieval models optimized for performance.
... | [
"### snowflake-arctic-embed-xs\n\n\nThis tiny model packs quite the punch. Based on the all-MiniLM-L6-v2 model with only 22m parameters and 384 dimensions, this model should meet even the strictest latency/TCO budgets. Despite its size, its retrieval accuracy is closer to that of models with 100m paramers.\n\n\n\nD... | [
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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": []} | lhallee/PIT_cifar_benchmark | null | [
"transformers",
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["trl", "orpo", "generated_from_trainer"], "datasets": ["argilla/distilabel-capybara-dpo-7k-binarized"], "base_model": "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1", "quantized_by": "mradermacher"} | mradermacher/zephyr-orpo-141b-A35b-v0.1-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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null | diffusers |
Orchwell is a Dance Diffusion model trained on an inexperienced orchestra with a disjoint sound.
It didn't go quite as well as expected, but it produces good samples 50-75% of the time.
It's also really the only current digital solution for making orchestra music that isn't perfectly composed (which makes it more uniq... | {"license": "lgpl-3.0", "library_name": "diffusers", "tags": ["audio-generation"]} | kronosta/orchwell | null | [
"diffusers",
"audio-generation",
"license:lgpl-3.0",
"region:us"
] | null | 2024-04-17T01:07:22+00:00 | [] | [] | TAGS
#diffusers #audio-generation #license-lgpl-3.0 #region-us
|
Orchwell is a Dance Diffusion model trained on an inexperienced orchestra with a disjoint sound.
It didn't go quite as well as expected, but it produces good samples 50-75% of the time.
It's also really the only current digital solution for making orchestra music that isn't perfectly composed (which makes it more uniq... | [] | [
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] | [
22
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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. -->
# model_hh_usp3_dpo1
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_usp3_dpo1", "results": []}]} | guoyu-zhang/model_hh_usp3_dpo1 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-17T01:07:49+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_usp3\_dpo1
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9835
* Rewards/chosen: -10.6241
* Rewards/rejected: -14.4122
* Rewards/accuracies: 0.7300
* Rewards/margins: 3.788... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\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. -->
# mistral7binstruct_summarize
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mi... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral7binstruct_summarize", "results": []}]} | rajkstats/mistral7binstruct_summarize | null | [
"peft",
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"trl",
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"generated_from_trainer",
"dataset:generator",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T01:08:03+00:00 | [] | [] | TAGS
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| mistral7binstruct\_summarize
============================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4540
Model description
-----------------
More information needed
Intended uses & limit... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_step... | [
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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": []} | thusinh1969/flant5xl-instruct-15MAR2024 | null | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-17T01:08:56+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
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text-generation | transformers |
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="https://github.com/deepseek-ai/DeepSeek-LLM/blob/main/images/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://chat.deepseek.com/">[🤖 Chat with DeepSeek LLM]</a> | <a href="https://disc... | {"license": "other", "license_name": "deepseek", "license_link": "https://github.com/deepseek-ai/DeepSeek-Math/blob/main/LICENSE-MODEL"} | blockblockblock/deepseek-math-7b-rl-bpw4.6 | null | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:2402.03300",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-17T01:10:12+00:00 | [
"2402.03300"
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#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<img width="500px" alt="DeepSeek Chat" src="URL
</p>
<p align="center"><a href="URL | <a href="URL Chat with DeepSeek LLM]</a> | <a href="URL | <a href="URL(微信)]</a> </p>
<p align="center">
<a href="URL Link</b>️</a>
</p>
<hr>
### 1. Introduction to DeepSeekMath
See the Introduction ... | [
"### 1. Introduction to DeepSeekMath\nSee the Introduction for more details.",
"### 2. How to Use\nHere give some examples of how to use our model.\n\nChat Completion\n\n Please use chain-of-thought prompt to test DeepSeekMath-Instruct and DeepSeekMath-RL:\n\n- English questions: {question}\\nPlease reason step b... | [
"TAGS\n#transformers #pytorch #safetensors #llama #text-generation #conversational #arxiv-2402.03300 #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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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_EMP_H3K36me3-seqsight_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M]... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_32768_512_43M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-17T01:11:39+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_32768\_512\_43M-L32\_all
=====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6535
*... | [
"### 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",
... | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us \n",
"### 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... | [
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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. -->
# mistral7binstruct_summarize
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mi... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral7binstruct_summarize", "results": []}]} | philmui/mistral7binstruct_summarize | null | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-17T01:15:30+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
| mistral7binstruct\_summarize
============================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4582
Model description
-----------------
More information needed
Intended uses & limit... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch... | [
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"TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_siz... |
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_32768_512_43M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_mouse_0-seqsight_32768_512_43M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_32768_512_43M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-17T01:16:00+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_mouse\_0-seqsight\_32768\_512\_43M-L32\_all
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 2.4951
* F1 Score: 0.62... | [
"### 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",
... | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us \n",
"### 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... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us \n### 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* opti... |
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. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "datas... | ryanjyc/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"base_model:distilbert-base-uncased",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-17T01:18:50+00:00 | [] | [] | TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #dataset-emotion #base_model-distilbert-base-uncased #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2117
* Accuracy: 0.929
* F1: 0.9289
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
"TAGS\n#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #dataset-emotion #base_model-distilbert-base-uncased #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters wer... | [
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"TAGS\n#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #dataset-emotion #base_model-distilbert-base-uncased #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used... |
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