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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
| {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.5 | null | [
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"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T10:19:15+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # GreenBit LLMs
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
| [
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low... | {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-3.0 | null | [
"transformers",
"safetensors",
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"license:apache-2.0",
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"region:us"
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#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GreenBit LLMs
=============
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using... | [
"### Zero-shot Evaluation\n\n\nWe evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using the 'llm\\_eval' library and list the results below:"
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tomaszki/stablelm-30 | null | [
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#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tomaszki/stablelm-30-a | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | mlx |
# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.2`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.2) for more details on the model.
## Use with mlx
... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.2-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-13T10:25:29+00:00 | [] | [] | TAGS
#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.2']().
Refer to the original model card for more details on the model.
## Use with mlx
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] |
text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low... | {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-3.0 | null | [
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"safetensors",
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"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T10:26:34+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GreenBit LLMs
=============
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using... | [
"### Zero-shot Evaluation\n\n\nWe evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using the 'llm\\_eval' library and list the results below:"
] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low... | {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.5 | null | [
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"safetensors",
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"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T10:26:44+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GreenBit LLMs
=============
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using... | [
"### Zero-shot Evaluation\n\n\nWe evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using the 'llm\\_eval' library and list the results below:"
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low... | {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-14B-Chat-layer-mix-bpw-2.2 | null | [
"transformers",
"safetensors",
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"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T10:26:52+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GreenBit LLMs
=============
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using... | [
"### Zero-shot Evaluation\n\n\nWe evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using the 'llm\\_eval' library and list the results below:"
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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-multilingual-cased_classification_finetuned_news_all_adptive
This model is a fine-tuned version of [distilbert/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "distilbert/distilbert-base-multilingual-cased", "model-index": [{"name": "distilbert-base-multilingual-cased_classification_finetuned_news_all_adptive", "results": []}]} | Mou11209203/distilbert-base-multilingual-cased_classification_finetuned_news_all_adptive | null | [
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| distilbert-base-multilingual-cased\_classification\_finetuned\_news\_all\_adptive
=================================================================================
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evalua... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-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: cosine\n* lr\\_scheduler\\_warmup\\_steps... | [
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text-generation | transformers |
# Ghost 7B Alpha
<img src="https://cdn-uploads.huggingface.co/production/uploads/600ae38cc92b79f54efd4556/QPrQZMQX_jzyYngmreP0_.jpeg" alt="Ghost 7B Alpha Logo" width="400" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
The large generation of language models focuses on optimizing excellent reasonin... | {"language": ["en", "vi"], "license": "other", "library_name": "transformers", "tags": ["ghost", "tools", "chat"], "license_name": "ghost-7b", "license_link": "https://ghost-x.org/ghost-7b-license", "pipeline_tag": "text-generation", "widget": [{"text": "Why is the sky blue ?", "output": {"text": "The sky appears blue ... | ghost-x/ghost-7b-alpha | null | [
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"conversational",
"en",
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"autotrain_compatible",
"endpoints_compatible",
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| Ghost 7B Alpha
==============
<img src="URL alt="Ghost 7B Alpha Logo" width="400" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
The large generation of language models focuses on optimizing excellent reasoning, multi-task knowledge, and tools support.
Introduction
============
Ghost 7B Alpha ... | [
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image-segmentation | null |
## This repo holds the official model weights of "[<ins>Bilateral Reference for High-Resolution Dichotomous Image Segmentation</ins>](https://arxiv.org/pdf/2401.03407.pdf)" (_arXiv 2024_).
This repo contains the weights of BiRefNet proposed in our paper, which has achieved the SOTA performance on three tasks (DIS, HR... | {"language": ["en"], "license": "mit", "tags": ["dichotomous-image-segmentation", "salient-object-detection", "camouflaged-object-detection", "image-matting"], "pipeline_tag": "image-segmentation"} | ZhengPeng7/BiRefNet | null | [
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"camouflaged-object-detection",
"image-matting",
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|
## This repo holds the official model weights of "<ins>Bilateral Reference for High-Resolution Dichotomous Image Segmentation</ins>" (_arXiv 2024_).
This repo contains the weights of BiRefNet proposed in our paper, which has achieved the SOTA performance on three tasks (DIS, HRSOD, and COD).
Go to my GitHub page for... | [
"## This repo holds the official model weights of \"<ins>Bilateral Reference for High-Resolution Dichotomous Image Segmentation</ins>\" (_arXiv 2024_).\n\nThis repo contains the weights of BiRefNet proposed in our paper, which has achieved the SOTA performance on three tasks (DIS, HRSOD, and COD).\n\nGo to my GitHu... | [
"TAGS\n#dichotomous-image-segmentation #salient-object-detection #camouflaged-object-detection #image-matting #image-segmentation #en #arxiv-2401.03407 #license-mit #region-us \n",
"## This repo holds the official model weights of \"<ins>Bilateral Reference for High-Resolution Dichotomous Image Segmentation</ins>... | [
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"TAGS\n#dichotomous-image-segmentation #salient-object-detection #camouflaged-object-detection #image-matting #image-segmentation #en #arxiv-2401.03407 #license-mit #region-us \n## This repo holds the official model weights of \"<ins>Bilateral Reference for High-Resolution Dichotomous Image Segmentation</ins>\" (_a... |
null | null | One of the most effective methods is to use a professional DataVare MBOX to HTML Converter to convert an MBOX file into an HTML file and access it in any web browsers like - chrome, Yahoo, etc. Users can utilize a tool that facilitates this process by using its advanced technical features. There are various third-party... | {} | DataVare/mbox-to-html-converter | null | [
"region:us"
] | null | 2024-04-13T10:46:02+00:00 | [] | [] | TAGS
#region-us
| One of the most effective methods is to use a professional DataVare MBOX to HTML Converter to convert an MBOX file into an HTML file and access it in any web browsers like - chrome, Yahoo, etc. Users can utilize a tool that facilitates this process by using its advanced technical features. There are various third-party... | [] | [
"TAGS\n#region-us \n"
] | [
5
] | [
"TAGS\n#region-us \n"
] |
text-classification | transformers |
# Model Card for Model ID
<!-- -->
Fine-tuned BERT trained to identify political party from speech in the UK Parliament. Trained with Labour/Conservative speeches using the hansard dataset 2000-2020
## Model Details
- **License:** MIT
- **Finetuned from model :** BERT
### Model Sources
<!-- Provide the basic li... | {"library_name": "transformers", "tags": ["politics", "parliamnet", "sentiment-analysis"]} | sisyphus199/ukparliamentBERT | null | [
"transformers",
"safetensors",
"bert",
"text-classification",
"politics",
"parliamnet",
"sentiment-analysis",
"arxiv:2010.05338",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T10:46:37+00:00 | [
"2010.05338"
] | [] | TAGS
#transformers #safetensors #bert #text-classification #politics #parliamnet #sentiment-analysis #arxiv-2010.05338 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
Fine-tuned BERT trained to identify political party from speech in the UK Parliament. Trained with Labour/Conservative speeches using the hansard dataset 2000-2020
## Model Details
- License: MIT
- Finetuned from model : BERT
### Model Sources
- Repository: Available on Github
## ... | [
"# Model Card for Model ID\n\n\nFine-tuned BERT trained to identify political party from speech in the UK Parliament. Trained with Labour/Conservative speeches using the hansard dataset 2000-2020",
"## Model Details\n\n- License: MIT\n- Finetuned from model : BERT",
"### Model Sources\n\n\n\n- Repository: Avail... | [
"TAGS\n#transformers #safetensors #bert #text-classification #politics #parliamnet #sentiment-analysis #arxiv-2010.05338 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Card for Model ID\n\n\nFine-tuned BERT trained to identify political party from speech in the UK Parliament. Trained with La... | [
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16,
13,
30,
37,
12,
14,
127
] | [
"TAGS\n#transformers #safetensors #bert #text-classification #politics #parliamnet #sentiment-analysis #arxiv-2010.05338 #autotrain_compatible #endpoints_compatible #region-us \n# Model Card for Model ID\n\n\nFine-tuned BERT trained to identify political party from speech in the UK Parliament. Trained with Labour/C... |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/ICBU-NPU/FashionGPT-70B-V1
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/FashionGPT-70B... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "datasets": ["ehartford/samantha-data", "Open-Orca/OpenOrca", "jondurbin/airoboros-gpt4-1.4.1"], "base_model": "ICBU-NPU/FashionGPT-70B-V1", "quantized_by": "mradermacher"} | mradermacher/FashionGPT-70B-V1-i1-GGUF | null | [
"transformers",
"gguf",
"en",
"dataset:ehartford/samantha-data",
"dataset:Open-Orca/OpenOrca",
"dataset:jondurbin/airoboros-gpt4-1.4.1",
"base_model:ICBU-NPU/FashionGPT-70B-V1",
"license:llama2",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T10:49:37+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #dataset-ehartford/samantha-data #dataset-Open-Orca/OpenOrca #dataset-jondurbin/airoboros-gpt4-1.4.1 #base_model-ICBU-NPU/FashionGPT-70B-V1 #license-llama2 #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
"TAGS\n#transformers #gguf #en #dataset-ehartford/samantha-data #dataset-Open-Orca/OpenOrca #dataset-jondurbin/airoboros-gpt4-1.4.1 #base_model-ICBU-NPU/FashionGPT-70B-V1 #license-llama2 #endpoints_compatible #region-us \n"
] | [
89
] | [
"TAGS\n#transformers #gguf #en #dataset-ehartford/samantha-data #dataset-Open-Orca/OpenOrca #dataset-jondurbin/airoboros-gpt4-1.4.1 #base_model-ICBU-NPU/FashionGPT-70B-V1 #license-llama2 #endpoints_compatible #region-us \n"
] |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/Fredithefish/FishxInstruct
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/FishxInstruct-... | {"language": ["en"], "library_name": "transformers", "base_model": "Fredithefish/FishxInstruct", "quantized_by": "mradermacher"} | mradermacher/FishxInstruct-i1-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:Fredithefish/FishxInstruct",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T10:49:41+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-Fredithefish/FishxInstruct #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
"TAGS\n#transformers #gguf #en #base_model-Fredithefish/FishxInstruct #endpoints_compatible #region-us \n"
] | [
33
] | [
"TAGS\n#transformers #gguf #en #base_model-Fredithefish/FishxInstruct #endpoints_compatible #region-us \n"
] |
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. -->
# imdb_classification_on_5M_full_pretrained_best_epoch_f1
This model is a fine-tuned version of [BigTMiami/amazon_pretraining_5M_m... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "BigTMiami/amazon_pretraining_5M_model_corrected", "model-index": [{"name": "imdb_classification_on_5M_full_pretrained_best_epoch_f1", "results": []}]} | ltuzova/imdb_classification_on_5M_full_pretrained_best_epoch_f1 | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:BigTMiami/amazon_pretraining_5M_model_corrected",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T10:51:17+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-BigTMiami/amazon_pretraining_5M_model_corrected #license-mit #autotrain_compatible #endpoints_compatible #region-us
| imdb\_classification\_on\_5M\_full\_pretrained\_best\_epoch\_f1
===============================================================
This model is a fine-tuned version of BigTMiami/amazon\_pretraining\_5M\_model\_corrected on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2685
* A... | [
"### 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:... | [
"TAGS\n#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-BigTMiami/amazon_pretraining_5M_model_corrected #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used durin... | [
62,
119,
5,
44
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"TAGS\n#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-BigTMiami/amazon_pretraining_5M_model_corrected #license-mit #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during trai... |
null | mlx |
# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5) for more details on the model.
## Use with mlx
... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-13T10:52:30+00:00 | [] | [] | TAGS
#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5-mlx\nThis quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5']().\nRefer to the original model card for more details on the model.",
"## Use with mlx"
] | [
"TAGS\n#mlx #safetensors #qwen2 #license-apache-2.0 #region-us \n",
"# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5-mlx\nThis quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5']().\nRefer to the original model card for more details on the model.",
"## Use ... | [
24,
90,
6
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"TAGS\n#mlx #safetensors #qwen2 #license-apache-2.0 #region-us \n# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5-mlx\nThis quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-2.5']().\nRefer to the original model card for more details on the model.## Use with mlx"
] |
null | null |
# DavidAU/Confinus-2x7B-Q4_K_M-GGUF
This model was converted to GGUF format from [`NeuralNovel/Confinus-2x7B`](https://huggingface.co/NeuralNovel/Confinus-2x7B) 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://huggin... | {"language": ["en"], "license": "apache-2.0", "tags": ["moe", "merge", "llama-cpp", "gguf-my-repo"], "model-index": [{"name": "Confinus-2x7B", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge... | DavidAU/Confinus-2x7B-Q4_K_M-GGUF | null | [
"gguf",
"moe",
"merge",
"llama-cpp",
"gguf-my-repo",
"en",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2024-04-13T10:53:51+00:00 | [] | [
"en"
] | TAGS
#gguf #moe #merge #llama-cpp #gguf-my-repo #en #license-apache-2.0 #model-index #region-us
|
# DavidAU/Confinus-2x7B-Q4_K_M-GGUF
This model was converted to GGUF format from 'NeuralNovel/Confinus-2x7B' 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/Confinus-2x7B-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'NeuralNovel/Confinus-2x7B' 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\nCLI:... | [
"TAGS\n#gguf #moe #merge #llama-cpp #gguf-my-repo #en #license-apache-2.0 #model-index #region-us \n",
"# DavidAU/Confinus-2x7B-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'NeuralNovel/Confinus-2x7B' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on th... | [
42,
79,
52
] | [
"TAGS\n#gguf #moe #merge #llama-cpp #gguf-my-repo #en #license-apache-2.0 #model-index #region-us \n# DavidAU/Confinus-2x7B-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'NeuralNovel/Confinus-2x7B' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the mode... |
text-generation | transformers | # What is is?
A MoE model for Roleplaying. Since 7B model is small enough, we can combine them to a bigger model (Which CAN be smarter).
Adapte (some limited) TSF (Trans Sexual Fiction) content because I have include my pre-train model in.
Better than V2 BTW.
# GGUF Version?
[Here](https://huggingface.co/Alsebay/Na... | {"license": "cc-by-nc-4.0", "tags": ["moe", "merge", "roleplay", "Roleplay"], "base_model": ["Alsebay/NarumashiRTS-V2", "SanjiWatsuki/Kunoichi-DPO-v2-7B", "Nitral-AI/KukulStanta-7B"]} | Alsebay/NaruMOE-v1-3x7B | null | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"merge",
"roleplay",
"Roleplay",
"base_model:Alsebay/NarumashiRTS-V2",
"base_model:SanjiWatsuki/Kunoichi-DPO-v2-7B",
"base_model:Nitral-AI/KukulStanta-7B",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compati... | null | 2024-04-13T10:54:01+00:00 | [] | [] | TAGS
#transformers #safetensors #mixtral #text-generation #moe #merge #roleplay #Roleplay #base_model-Alsebay/NarumashiRTS-V2 #base_model-SanjiWatsuki/Kunoichi-DPO-v2-7B #base_model-Nitral-AI/KukulStanta-7B #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # What is is?
A MoE model for Roleplaying. Since 7B model is small enough, we can combine them to a bigger model (Which CAN be smarter).
Adapte (some limited) TSF (Trans Sexual Fiction) content because I have include my pre-train model in.
Better than V2 BTW.
# GGUF Version?
Here
# Recipe?
You could see base model... | [
"# What is is?\n\nA MoE model for Roleplaying. Since 7B model is small enough, we can combine them to a bigger model (Which CAN be smarter).\n\nAdapte (some limited) TSF (Trans Sexual Fiction) content because I have include my pre-train model in.\n\nBetter than V2 BTW.",
"# GGUF Version?\nHere",
"# Recipe?\n\nY... | [
"TAGS\n#transformers #safetensors #mixtral #text-generation #moe #merge #roleplay #Roleplay #base_model-Alsebay/NarumashiRTS-V2 #base_model-SanjiWatsuki/Kunoichi-DPO-v2-7B #base_model-Nitral-AI/KukulStanta-7B #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"... | [
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"TAGS\n#transformers #safetensors #mixtral #text-generation #moe #merge #roleplay #Roleplay #base_model-Alsebay/NarumashiRTS-V2 #base_model-SanjiWatsuki/Kunoichi-DPO-v2-7B #base_model-Nitral-AI/KukulStanta-7B #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n#... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **BipedalWalker-v3**
This is a trained model of a **PPO** agent playing **BipedalWalker-v3**
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_... | {"library_name": "stable-baselines3", "tags": ["BipedalWalker-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "Bi... | koopatroopa787/ppo-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-13T10:56:15+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing BipedalWalker-v3
This is a trained model of a PPO agent playing BipedalWalker-v3
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing BipedalWalker-v3\nThis is a trained model of a PPO agent playing BipedalWalker-v3\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing BipedalWalker-v3\nThis is a trained model of a PPO agent playing BipedalWalker-v3\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: A... | [
33,
39,
17
] | [
"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# PPO Agent playing BipedalWalker-v3\nThis is a trained model of a PPO agent playing BipedalWalker-v3\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add your code... |
text-generation | transformers |
# Model Card for Model ID
This is a model of the google Gemma-7B model with the parameter size increased to 14B. The attention head has been doubled and the number of hidden layers has been increased to 42.
# Chat template
**system:** system message...
**B:** user message...
**A:** assistant message... | {"language": ["ko"], "license": "apache-2.0", "library_name": "transformers"} | lcw99/google-gemma-14B-ko-chang | null | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"conversational",
"ko",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T10:57:35+00:00 | [] | [
"ko"
] | TAGS
#transformers #safetensors #gemma #text-generation #conversational #ko #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
This is a model of the google Gemma-7B model with the parameter size increased to 14B. The attention head has been doubled and the number of hidden layers has been increased to 42.
# Chat template
system: system message...
B: user message...
A: assistant message... | [
"# Model Card for Model ID\n\nThis is a model of the google Gemma-7B model with the parameter size increased to 14B. The attention head has been doubled and the number of hidden layers has been increased to 42.",
"# Chat template\n\nsystem: system message... \nB: user message... \nA: assistant message..."
] | [
"TAGS\n#transformers #safetensors #gemma #text-generation #conversational #ko #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID\n\nThis is a model of the google Gemma-7B model with the parameter size increased to 14B. The attentio... | [
46,
45,
24
] | [
"TAGS\n#transformers #safetensors #gemma #text-generation #conversational #ko #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n# Model Card for Model ID\n\nThis is a model of the google Gemma-7B model with the parameter size increased to 14B. The attention head... |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Eliorkalfon/code-math-7B-slerp
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not s... | {"language": ["en"], "library_name": "transformers", "base_model": "Eliorkalfon/code-math-7B-slerp", "quantized_by": "mradermacher"} | mradermacher/code-math-7B-slerp-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:Eliorkalfon/code-math-7B-slerp",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T11:01:35+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-Eliorkalfon/code-math-7B-slerp #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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null | null |
# DavidAU/DarkForest-20B-v2.0-Q5_K_M-GGUF
This model was converted to GGUF format from [`TeeZee/DarkForest-20B-v2.0`](https://huggingface.co/TeeZee/DarkForest-20B-v2.0) 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:... | {"license": "other", "tags": ["merge", "not-for-all-audiences", "llama-cpp", "gguf-my-repo"], "license_name": "microsoft-research-license", "model-index": [{"name": "DarkForest-20B-v2.0", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)"... | DavidAU/DarkForest-20B-v2.0-Q5_K_M-GGUF | null | [
"gguf",
"merge",
"not-for-all-audiences",
"llama-cpp",
"gguf-my-repo",
"license:other",
"model-index",
"region:us"
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#gguf #merge #not-for-all-audiences #llama-cpp #gguf-my-repo #license-other #model-index #region-us
|
# DavidAU/DarkForest-20B-v2.0-Q5_K_M-GGUF
This model was converted to GGUF format from 'TeeZee/DarkForest-20B-v2.0' 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:... | [
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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": []} | abhayesian/BobzillaV14 | null | [
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"endpoints_compatible",
"region:us"
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tomaszki/mistral-31-a | 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:
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null | mlx |
# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-3.0`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-3.0) for more details on the model.
## Use with mlx
... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-3.0-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"license:apache-2.0",
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#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-4B-Chat-layer-mix-bpw-3.0']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
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] |
null | null | ToolsBaer OLM to MBOX Conversion is a great application available for converting OLM data to MBOX format. It is easy and safe to convert any large OLM file to the MBOX format. 100% correctness can be achieved while converting OLM files to MBOX files. Anything related to emails that can be stored in an OLM file, includi... | {} | madelineoliver/ToolsBaer-OLM-to-MBOX-Conversion | null | [
"region:us"
] | null | 2024-04-13T11:07:24+00:00 | [] | [] | TAGS
#region-us
| ToolsBaer OLM to MBOX Conversion is a great application available for converting OLM data to MBOX format. It is easy and safe to convert any large OLM file to the MBOX format. 100% correctness can be achieved while converting OLM files to MBOX files. Anything related to emails that can be stored in an OLM file, includi... | [] | [
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image-classification | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metrics
loss: 0.2612117528915405
f1_macro: 0.5509939923795275
f1_micro: 0.9278878255063432
f1_weighted: 0.915533252030031
precision_macro: 0.7507175360173887
precision_micro: 0.9278878255063432
precision_weighted: 0.918485918511... | {"tags": ["autotrain", "image-classification"], "datasets": ["xblock-social-screenshots-5/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg",... | howdyaendra/xblock-social-screenshots-5 | null | [
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#transformers #tensorboard #safetensors #vit #image-classification #autotrain #dataset-xblock-social-screenshots-5/autotrain-data #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metrics
loss: 0.2612117528915405
f1_macro: 0.5509939923795275
f1_micro: 0.9278878255063432
f1_weighted: 0.915533252030031
precision_macro: 0.7507175360173887
precision_micro: 0.9278878255063432
precision_weighted: 0.918485918511... | [
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null | mlx |
# GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0) for more details on the model.
## Use wit... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-13T11:07:39+00:00 | [] | [] | TAGS
#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0-mlx\nThis quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-3.0']().\nRefer to the original model card for more details on the model.",
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null | mlx |
# GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.5`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.5) for more details on the model.
## Use wit... | {"tags": ["mlx"]} | GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.5-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"region:us"
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#mlx #safetensors #qwen2 #region-us
|
# GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.5']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
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null | transformers |
# Uploaded model
- **Developed by:** raosharjeel
- **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/uns... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | raosharjeel/tonymatrixmixtral2 | null | [
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|
# Uploaded model
- Developed by: raosharjeel
- 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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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": []} | Zardian/Cyber_assist3.2 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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text-generation | transformers |
# Uploaded model
- **Developed by:** ntvcie
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b
This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl"], "base_model": "unsloth/gemma-2b"} | ntvcie/Gemma2bVinhntV3_16bit | null | [
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"license:apache-2.0",
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"region:us"
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"en"
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|
# Uploaded model
- Developed by: ntvcie
- License: apache-2.0
- Finetuned from model : unsloth/gemma-2b
This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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] | [
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null | null |
# DavidAU/DarkForest-20B-v1.0-Q5_K_M-GGUF
This model was converted to GGUF format from [`TeeZee/DarkForest-20B-v1.0`](https://huggingface.co/TeeZee/DarkForest-20B-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:... | {"license": "other", "tags": ["merge", "not-for-all-audiences", "llama-cpp", "gguf-my-repo"], "license_name": "microsoft-research-license"} | DavidAU/DarkForest-20B-v1.0-Q5_K_M-GGUF | null | [
"gguf",
"merge",
"not-for-all-audiences",
"llama-cpp",
"gguf-my-repo",
"license:other",
"region:us"
] | null | 2024-04-13T11:14:41+00:00 | [] | [] | TAGS
#gguf #merge #not-for-all-audiences #llama-cpp #gguf-my-repo #license-other #region-us
|
# DavidAU/DarkForest-20B-v1.0-Q5_K_M-GGUF
This model was converted to GGUF format from 'TeeZee/DarkForest-20B-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:... | [
"# DavidAU/DarkForest-20B-v1.0-Q5_K_M-GGUF\nThis model was converted to GGUF format from 'TeeZee/DarkForest-20B-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 server or the CLI.\... | [
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audio-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-small-dialect-classifier-cross
This model is a fine-tuned version of [yaygomii/whisper-small-ta-fyp](https://huggingface... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "yaygomii/whisper-small-ta-fyp", "model-index": [{"name": "whisper-small-dialect-classifier-cross", "results": []}]} | yaygomii/whisper-small-dialect-classifier-cross | null | [
"transformers",
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"safetensors",
"whisper",
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"generated_from_trainer",
"base_model:yaygomii/whisper-small-ta-fyp",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T11:15:30+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #whisper #audio-classification #generated_from_trainer #base_model-yaygomii/whisper-small-ta-fyp #license-apache-2.0 #endpoints_compatible #region-us
| whisper-small-dialect-classifier-cross
======================================
This model is a fine-tuned version of yaygomii/whisper-small-ta-fyp on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0010
* Accuracy: 1.0
Model description
-----------------
More information ne... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio... | [
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null | null |
Merge the QLoRA adpter model with the corrsponding Baichuan2-13 Model before use.
Baichuan2-13B: https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat | {"license": "apache-2.0"} | cyysky2/Baichuan2-13B_SFT_on_DISC-Law | null | [
"tensorboard",
"license:apache-2.0",
"region:us"
] | null | 2024-04-13T11:16:16+00:00 | [] | [] | TAGS
#tensorboard #license-apache-2.0 #region-us
|
Merge the QLoRA adpter model with the corrsponding Baichuan2-13 Model before use.
Baichuan2-13B: URL | [] | [
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16
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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. -->
# multilingual-xlm-roberta-for-ner
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-bas... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "multilingual-xlm-roberta-for-ner", "results": []}]} | bcokdilli/multilingual-xlm-roberta-for-ner | null | [
"transformers",
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"xlm-roberta",
"token-classification",
"generated_from_trainer",
"base_model:xlm-roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2024-04-13T11:18:17+00:00 | [] | [] | TAGS
#transformers #safetensors #xlm-roberta #token-classification #generated_from_trainer #base_model-xlm-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us
| multilingual-xlm-roberta-for-ner
================================
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: 0.1383
* F1: 0.8620
Model description
-----------------
More information needed
Intended uses & limit... | [
"### 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 |
# DavidAU/Buttocks-7B-v1.0-Q4_K_M-GGUF
This model was converted to GGUF format from [`TeeZee/Buttocks-7B-v1.0`](https://huggingface.co/TeeZee/Buttocks-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": "cc-by-nc-4.0", "tags": ["not-for-all-audiences", "merge", "llama-cpp", "gguf-my-repo"], "model-index": [{"name": "Buttocks-7B-v1.0", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challe... | DavidAU/Buttocks-7B-v1.0-Q4_K_M-GGUF | null | [
"gguf",
"not-for-all-audiences",
"merge",
"llama-cpp",
"gguf-my-repo",
"license:cc-by-nc-4.0",
"model-index",
"region:us"
] | null | 2024-04-13T11:19:32+00:00 | [] | [] | TAGS
#gguf #not-for-all-audiences #merge #llama-cpp #gguf-my-repo #license-cc-by-nc-4.0 #model-index #region-us
|
# DavidAU/Buttocks-7B-v1.0-Q4_K_M-GGUF
This model was converted to GGUF format from 'TeeZee/Buttocks-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:
No... | [
"# DavidAU/Buttocks-7B-v1.0-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'TeeZee/Buttocks-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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"TAGS\n#gguf #not-for-all-audiences #merge #llama-cpp #gguf-my-repo #license-cc-by-nc-4.0 #model-index #region-us \n# DavidAU/Buttocks-7B-v1.0-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'TeeZee/Buttocks-7B-v1.0' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more de... |
text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tomaszki/mistral-31 | null | [
"transformers",
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"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T11:19:34+00:00 | [
"1910.09700"
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Psoriasis-Project-Aug-M-vit-large-patch16-224-in21k
This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](h... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-large-patch16-224-in21k", "model-index": [{"name": "Psoriasis-Project-Aug-M-vit-large-patch16-224-in21k", "results": []}]} | ahmedesmail16/Psoriasis-Project-Aug-M-vit-large-patch16-224-in21k | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T11:19:50+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #vit #image-classification #generated_from_trainer #base_model-google/vit-large-patch16-224-in21k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| Psoriasis-Project-Aug-M-vit-large-patch16-224-in21k
===================================================
This model is a fine-tuned version of google/vit-large-patch16-224-in21k on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0055
* Accuracy: 1.0
Model description
--------... | [
"### 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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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... | Aqel/distilbert-base-uncased-finetuned-emotion | null | [
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"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T11:20:09+00:00 | [] | [] | TAGS
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| 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: 0.2146
* Accuracy: 0.9255
* F1: 0.9255
Model description
-----------------
Mo... | [
"### 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... | [
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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. -->
# outputs
This model is a fine-tuned version of [unsloth/gemma-2b-bnb-4bit](https://huggingface.co/unsloth/gemma-2b-bnb-4bit) on a... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "unsloth", "generated_from_trainer"], "base_model": "unsloth/gemma-2b-bnb-4bit", "model-index": [{"name": "outputs", "results": []}]} | manasikhillare/python_qna_finetuned_gemma | null | [
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"generated_from_trainer",
"base_model:unsloth/gemma-2b-bnb-4bit",
"license:apache-2.0",
"region:us"
] | null | 2024-04-13T11:20:41+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #unsloth #generated_from_trainer #base_model-unsloth/gemma-2b-bnb-4bit #license-apache-2.0 #region-us
|
# outputs
This model is a fine-tuned version of unsloth/gemma-2b-bnb-4bit on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The... | [
"# outputs\n\nThis model is a fine-tuned version of unsloth/gemma-2b-bnb-4bit 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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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | jhovany/Beto_Clasificar_Tweets_Mexicanos_Homomex2024 | null | [
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"bert",
"text-classification",
"arxiv:1910.09700",
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"1910.09700"
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#transformers #safetensors #bert #text-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tomaszki/mistral-31-b | null | [
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"text-generation",
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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... | stanoh/distilbert-base-uncased-finetuned-emotion | null | [
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| 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: 0.2178
* Accuracy: 0.9275
* F1: 0.9275
Model description
-----------------
Mo... | [
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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": ["axolotl", "generated_from_trainer"], "base_model": "unsloth/gemma-7b", "model-index": [{"name": "gemma_odia_7b_unsloth", "results": []}]} | OdiaGenAI-LLM/odia-gemma-7b-base-checkpoints | null | [
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#peft #safetensors #gemma #axolotl #generated_from_trainer #base_model-unsloth/gemma-7b #license-apache-2.0 #4-bit #region-us
| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
gemma\_odia\_7b\_unsloth
========================
This model is a fine-tuned version of unsloth/gemma-7b on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.9914
... | [
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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-multilingual-cased_classification_finetuned_dcard_adptive
This model is a fine-tuned version of [distilbert/dist... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "distilbert/distilbert-base-multilingual-cased", "model-index": [{"name": "distilbert-base-multilingual-cased_classification_finetuned_dcard_adptive", "results": []}]} | Mou11209203/distilbert-base-multilingual-cased_classification_finetuned_dcard_adptive | null | [
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| distilbert-base-multilingual-cased\_classification\_finetuned\_dcard\_adptive
=============================================================================
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on an unknown dataset.
It achieves the following results on the evaluation set... | [
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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": []} | baris-yazici/binary_liar_TinyLlama_TinyLlama-1.1B-Chat-v1.0_PROMPT_TUNING_CAUSAL_LM | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
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"1910.09700"
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | HenryCai1129/lora-test | null | [
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## 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 | mlx |
# GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-3.0`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-3.0) for more details on the model.
## Use with mlx
... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-3.0-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"license:apache-2.0",
"region:us"
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#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-3.0']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
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] |
text-generation | transformers |
# Inex12Mergerix-7B
Inex12Mergerix-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [MSL7/INEX12-7b](https://huggingface.co/MSL7/INEX12-7b)
* [MiniMoog/Mergerix-7b-v0.3](https://huggingface.co/MiniMoog/Mergerix-7b-v0.3)
## 🧩 Configuration
``... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"], "base_model": ["MSL7/INEX12-7b", "MiniMoog/Mergerix-7b-v0.3"]} | automerger/Inex12Mergerix-7B | null | [
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"license:apache-2.0",
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"text-generation-inference",
"region:... | null | 2024-04-13T11:43:58+00:00 | [] | [] | TAGS
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|
# Inex12Mergerix-7B
Inex12Mergerix-7B is an automated merge created by Maxime Labonne using the following configuration.
* MSL7/INEX12-7b
* MiniMoog/Mergerix-7b-v0.3
## Configuration
## Usage
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | dbaek111/llama2-lora-finetunined-merged_test | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | mlx |
# GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.2`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.2) for more details on the model.
## Use with mlx
... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.2-mlx | null | [
"mlx",
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"region:us"
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#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.2']().
Refer to the original model card for more details on the model.
## Use with mlx
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null | mlx |
# GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.5`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.5) for more details on the model.
## Use with mlx
... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.5-mlx | null | [
"mlx",
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#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-7B-Chat-layer-mix-bpw-2.5']().
Refer to the original model card for more details on the model.
## Use with mlx
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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": []} | OsakanaTeishoku/mixtral_small_dummy | null | [
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#transformers #safetensors #mixtral #text-generation #custom_code #arxiv-1910.09700 #autotrain_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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text-to-image | diffusers | # LuMiNAShaper
<Gallery />
## Download model
Weights for this model are available in Safetensors format.
[Download](/synthetica/luminashaper/tree/main) them in the Files & versions tab.
| {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "A photo of a sunny desert beach", "parameters": {"negative_prompt": "NSFW"}, "output": {"url": "images/A photo of a sunny desert beach.jpg"}}], "base_model": "dreamlike-art/dreamlike-photoreal-2.0"} | synthetica/luminashaper | null | [
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"stable-diffusion",
"lora",
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"base_model:dreamlike-art/dreamlike-photoreal-2.0",
"has_space",
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#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-dreamlike-art/dreamlike-photoreal-2.0 #has_space #region-us
| # LuMiNAShaper
<Gallery />
## Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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] |
text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - philipp-zettl/ssd-butters-lora
<Gallery />
## Model description
These are philipp-zettl/ssd-bu... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "lora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"], "base_model": "segmind/SSD-1B", "instance_prompt": "BUTTCC", "widget": []} | philipp-zettl/ssd-butters-lora | null | [
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"license:openrail++",
"region:us"
] | null | 2024-04-13T11:51:34+00:00 | [] | [] | TAGS
#diffusers #text-to-image #diffusers-training #lora #template-sd-lora #stable-diffusion-xl #stable-diffusion-xl-diffusers #base_model-segmind/SSD-1B #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - philipp-zettl/ssd-butters-lora
<Gallery />
## Model description
These are philipp-zettl/ssd-butters-lora LoRA adaption weights for segmind/SSD-1B.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: None.
## Trigger... | [
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# chaikit/food_classifier
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-ba... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "chaikit/food_classifier", "results": []}]} | chaikit/food_classifier | null | [
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| chaikit/food\_classifier
========================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 2.4037
* Validation Loss: 1.4256
* Train Accuracy: 0.884
* Epoch: 0
Model description
------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'module': 'keras.optimizers.schedules', 'class\\_name': 'PolynomialDecay', 'config': {'initial\\_learning\\_rate': 3e-05, 'decay\\_steps': 20000, 'end\\_learn... | [
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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-multilingual-cased_classification_finetuned_mobile01_all_adptive
This model is a fine-tuned version of [distilbe... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "distilbert/distilbert-base-multilingual-cased", "model-index": [{"name": "distilbert-base-multilingual-cased_classification_finetuned_mobile01_all_adptive", "results": []}]} | Mou11209203/distilbert-base-multilingual-cased_classification_finetuned_mobile01_all_adptive | null | [
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| distilbert-base-multilingual-cased\_classification\_finetuned\_mobile01\_all\_adptive
=====================================================================================
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on an unknown dataset.
It achieves the following results on th... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-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: cosine\n* lr\\_scheduler\\_warmup\\_steps... | [
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null | null | Arteris Plus Vidonge ni nini?
Arteris Plus kibonge ni nyongeza ya lishe ya mapinduzi iliyoundwa kusaidia afya ya moyo na mishipa. Imeundwa kwa ustadi kwa kutumia mchanganyiko wa viambato vya asili vinavyojulikana kwa athari zake za manufaa kwenye utendaji kazi wa moyo na udhibiti wa shinikizo la damu. Kirutubisho hiki... | {"license": "apache-2.0"} | ArterisPlus/ArterisPlus | null | [
"license:apache-2.0",
"region:us"
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#license-apache-2.0 #region-us
| Arteris Plus Vidonge ni nini?
Arteris Plus kibonge ni nyongeza ya lishe ya mapinduzi iliyoundwa kusaidia afya ya moyo na mishipa. Imeundwa kwa ustadi kwa kutumia mchanganyiko wa viambato vya asili vinavyojulikana kwa athari zake za manufaa kwenye utendaji kazi wa moyo na udhibiti wa shinikizo la damu. Kirutubisho hiki... | [] | [
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text-generation | transformers | # `Stable LM 2 BRIEF 1.6B`
Fine-tuned chat model based on `stabilityai/stablelm-2-1_6b`. It was trained for 21 epochs using 1024 context windows and a mixture of small subsets of UltraChat and OASST2. Since the model saw shorter dialogs it tends to be less verbose than StabilityAI's 1.6B chat model `stabilityai/stable... | {"language": ["en"], "license": "other", "tags": ["causal-lm"], "datasets": ["HuggingFaceH4/ultrachat_200k", "g-ronimo/oasst2_top4k_en"], "pipeline_tag": "text-generation"} | maxim-saplin/stablelm-2-brief-1_6b | null | [
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"dataset:g-ronimo/oasst2_top4k_en",
"license:other",
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| # 'Stable LM 2 BRIEF 1.6B'
Fine-tuned chat model based on 'stabilityai/stablelm-2-1_6b'. It was trained for 21 epochs using 1024 context windows and a mixture of small subsets of UltraChat and OASST2. Since the model saw shorter dialogs it tends to be less verbose than StabilityAI's 1.6B chat model 'stabilityai/stable... | [
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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. -->
# results
This model is a fine-tuned version of [jkhan447/sarcasm-detection-Bert-base-uncased](https://huggingface.co/jkhan447/sar... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "jkhan447/sarcasm-detection-Bert-base-uncased", "model-index": [{"name": "results", "results": []}]} | dianamihalache27/results | null | [
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|
# results
This model is a fine-tuned version of jkhan447/sarcasm-detection-Bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5616
- Accuracy: 0.7233
- F1: 0.4483
## Model description
More information needed
## Intended uses & limitations
More information... | [
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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. -->
# roberta-base-finetuned-classifier-roberta1
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "accuracy"], "base_model": "roberta-base", "model-index": [{"name": "roberta-base-finetuned-classifier-roberta1", "results": []}]} | gserafico/roberta-base-finetuned-classifier-roberta1 | null | [
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"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2024-04-13T11:58:55+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us
| roberta-base-finetuned-classifier-roberta1
==========================================
This model is a fine-tuned version of roberta-base on the lectures dataset.
It achieves the following results on the test set:
* Loss: 0.5266
* Precision: 0.9244
* Recall: 0.9200
* F1-score: 0.9198
* Accuracy: 0.92
Model descrip... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-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",
"### Traini... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... | [
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feature-extraction | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetuned_bge_ver10
This model is a fine-tuned version of [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3) on Vietnamese SQuAD ... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "BAAI/bge-m3", "model-index": [{"name": "finetuned_bge_ver10", "results": []}]} | comet24082002/finetuned_bge_ver10 | null | [
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"feature-extraction",
"generated_from_trainer",
"base_model:BAAI/bge-m3",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T12:01:53+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #xlm-roberta #feature-extraction #generated_from_trainer #base_model-BAAI/bge-m3 #license-mit #endpoints_compatible #region-us
|
# finetuned_bge_ver10
This model is a fine-tuned version of BAAI/bge-m3 on Vietnamese SQuAD dataset and 80% Zalo AI Legal Text dataset no segmented .
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## ... | [
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null | adapter-transformers |
# Adapter `BigTMiami/F_adapter_ia3_pretraining_P_20` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_split_25M_reviews_20_percent_condensed](https://huggingface.co/datasets/BigTMiami/amazon_split_25M_reviews_20_percent_condensed/) dataset and... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_split_25M_reviews_20_percent_condensed"]} | BigTMiami/F_adapter_ia3_pretraining_P_20 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_split_25M_reviews_20_percent_condensed",
"region:us"
] | null | 2024-04-13T12:02:19+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_split_25M_reviews_20_percent_condensed #region-us
|
# Adapter 'BigTMiami/F_adapter_ia3_pretraining_P_20' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_split_25M_reviews_20_percent_condensed dataset and includes a prediction head for masked lm.
This adapter was created for usage with the Adapters library.
## Usage
... | [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | jhovany/Beto_Clasificar_Tweets_Mexicanos_DataAumen_Homomex2024 | null | [
"transformers",
"safetensors",
"bert",
"text-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T12:04:50+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #bert #text-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | adapter-transformers |
# Adapter `BigTMiami/G_adapter_compactor_pretraining_P_20` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_split_25M_reviews_20_percent_condensed](https://huggingface.co/datasets/BigTMiami/amazon_split_25M_reviews_20_percent_condensed/) datas... | {"tags": ["adapter-transformers", "roberta"], "datasets": ["BigTMiami/amazon_split_25M_reviews_20_percent_condensed"]} | BigTMiami/G_adapter_compactor_pretraining_P_20 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_split_25M_reviews_20_percent_condensed",
"region:us"
] | null | 2024-04-13T12:07:43+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_split_25M_reviews_20_percent_condensed #region-us
|
# Adapter 'BigTMiami/G_adapter_compactor_pretraining_P_20' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_split_25M_reviews_20_percent_condensed dataset and includes a prediction head for masked lm.
This adapter was created for usage with the Adapters library.
## U... | [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilgpt2-finetuned-python_code_instructions_18k_alpaca
This model is a fine-tuned version of [distilgpt2](https://huggingface.... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["generated_from_trainer"], "datasets": ["iamtarun/python_code_instructions_18k_alpaca"], "metrics": ["accuracy"], "base_model": "distilgpt2", "pipeline_tag": "text-generation", "model-index": [{"name": "distilgpt2-finetuned-python_co... | Vishaltiwari2019/distilgpt2-finetuned-python_code_instructions_18k_alpaca | null | [
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"base_model:distilgpt2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"regi... | null | 2024-04-13T12:09:05+00:00 | [] | [
"en"
] | TAGS
#transformers #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #en #dataset-iamtarun/python_code_instructions_18k_alpaca #base_model-distilgpt2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| distilgpt2-finetuned-python\_code\_instructions\_18k\_alpaca
============================================================
This model is a fine-tuned version of distilgpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.5063
Model description
-----------------
More infor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-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",
"### Training... | [
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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:
* [WizardLM/WizardMath-7B-V1.1](https://huggin... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["WizardLM/WizardMath-7B-V1.1", "NousResearch/Hermes-2-Pro-Mistral-7B"]} | mergekit-community/mergekit-slerp-jgwqzez | null | [
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"base_model:NousResearch/Hermes-2-Pro-Mistral-7B",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-13T12:09:30+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #conversational #base_model-WizardLM/WizardMath-7B-V1.1 #base_model-NousResearch/Hermes-2-Pro-Mistral-7B #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:
* WizardLM/WizardMath-7B-V1.1
* NousResearch/Hermes-2-Pro-Mistral-7B
### Configura... | [
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text-to-image | diffusers |
# API Inference
## Get API Key
Get API key from [ModelsLab API](http://modelslab.com), No Payment needed.
Replace Key in below code, change **model_id** to "zavychromaxl-v6"
Coding in PHP/... | {"license": "creativeml-openrail-m", "tags": ["modelslab.com", "stable-diffusion-api", "text-to-image", "ultra-realistic"], "pinned": true} | stablediffusionapi/zavychromaxl-v6 | null | [
"diffusers",
"modelslab.com",
"stable-diffusion-api",
"text-to-image",
"ultra-realistic",
"license:creativeml-openrail-m",
"endpoints_compatible",
"has_space",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | null | 2024-04-13T12:09:35+00:00 | [] | [] | TAGS
#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us
|
# API Inference
!generated from URL
## Get API Key
Get API key from ModelsLab API, No Payment needed.
Replace Key in below code, change model_id to "zavychromaxl-v6"
Coding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs
Try model for free: Generate Images
Model link: View model
V... | [
"# API Inference\n\n!generated from URL",
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"TAGS\n#diffusers #modelslab.com #stable-diffusion-api #text-to-image #ultra-realistic #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionXLPipeline #region-us \n",
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# imdb_classification_on_25M_full_pretrained_best_epoch_f1
This model is a fine-tuned version of [ltuzova/amazon_domain_pretrained... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "ltuzova/amazon_domain_pretrained_model", "model-index": [{"name": "imdb_classification_on_25M_full_pretrained_best_epoch_f1", "results": []}]} | ltuzova/imdb_classification_on_25M_full_pretrained_best_epoch_f1 | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
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"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T12:12:17+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-ltuzova/amazon_domain_pretrained_model #license-mit #autotrain_compatible #endpoints_compatible #region-us
| imdb\_classification\_on\_25M\_full\_pretrained\_best\_epoch\_f1
================================================================
This model is a fine-tuned version of ltuzova/amazon\_domain\_pretrained\_model on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1535
* Accuracy:... | [
"### 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 | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/CultriX/MonaCeption-7B-SLERP-SFT
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not... | {"language": ["en"], "library_name": "transformers", "base_model": "CultriX/MonaCeption-7B-SLERP-SFT", "quantized_by": "mradermacher"} | mradermacher/MonaCeption-7B-SLERP-SFT-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:CultriX/MonaCeption-7B-SLERP-SFT",
"endpoints_compatible",
"region:us"
] | null | 2024-04-13T12:12:34+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-CultriX/MonaCeption-7B-SLERP-SFT #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
"TAGS\n#transformers #gguf #en #base_model-CultriX/MonaCeption-7B-SLERP-SFT #endpoints_compatible #region-us \n"
] | [
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] |
null | null | Just a mirror of files from https://github.com/Megvii-BaseDetection/YOLOX/blob/main/demo/ONNXRuntime/README.md | {"license": "apache-2.0"} | halffried/yolox | null | [
"onnx",
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#onnx #license-apache-2.0 #region-us
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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. -->
# amazon_kindle_sentiment_analysis_final
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-bas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "amazon_kindle_sentiment_analysis_final", "results": []}]} | denise227/amazon_kindle_sentiment_analysis_final | null | [
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| amazon\_kindle\_sentiment\_analysis\_final
==========================================
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9292
* Accuracy: 0.6083
Model description
-----------------
More information nee... | [
"### 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: 2",
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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. -->
# tinyllama-deepak
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/Tin... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "model-index": [{"name": "tinyllama-deepak", "results": []}]} | deepakdevfocaloid/tinyllama-deepak | null | [
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|
# tinyllama-deepak
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hype... | [
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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": []} | unrented5443/p96urzm | 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:
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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. -->
# results2
This model is a fine-tuned version of [jkhan447/sarcasm-detection-RoBerta-base](https://huggingface.co/jkhan447/sarcasm... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "jkhan447/sarcasm-detection-RoBerta-base", "model-index": [{"name": "results2", "results": []}]} | dianamihalache27/results2 | null | [
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|
# results2
This model is a fine-tuned version of jkhan447/sarcasm-detection-RoBerta-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6135
- Accuracy: 0.7133
- F1: 0.0
## Model description
More information needed
## Intended uses & limitations
More information needed... | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** prince-canuma
- **License:** apache-2.0
- **Finetuned from model :** prince-canuma/Damysus-Coder-v0.1
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/unslot... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "prince-canuma/Damysus-Coder-v0.1"} | prince-canuma/Damysus-Coder-v0.1-4bit | null | [
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|
# Uploaded model
- Developed by: prince-canuma
- License: apache-2.0
- Finetuned from model : prince-canuma/Damysus-Coder-v0.1
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-generation | transformers |
## Matter 7B - 0.2 - DPO (Mistral 7B Finetune)
DPO version of [Matter 7B](https://huggingface.co/0-hero/Matter-0.2-7B) fine-tuned on the [Matter dataset](https://huggingface.co/datasets/0-hero/Matter-0.2-alpha), which is curated from over 35 datsets analyzing >6B tokens
### Training
Prompt format: This model uses ... | {"language": ["en"], "license": "apache-2.0", "datasets": ["0-hero/Matter-0.2-alpha"]} | 0-hero/Matter-0.2-7B-DPO | null | [
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|
## Matter 7B - 0.2 - DPO (Mistral 7B Finetune)
DPO version of Matter 7B fine-tuned on the Matter dataset, which is curated from over 35 datsets analyzing >6B tokens
### Training
Prompt format: This model uses ChatML prompt format.
### Function Calling
Model also supports function calling. Additional tokens for f... | [
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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. -->
# amazon_helpfulness_classification_on_5M_full_pretrained_best_epoch_f1
This model is a fine-tuned version of [BigTMiami/amazon_pr... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "BigTMiami/amazon_pretraining_5M_model_corrected", "model-index": [{"name": "amazon_helpfulness_classification_on_5M_full_pretrained_best_epoch_f1", "results": []}]} | ltuzova/amazon_helpfulness_classification_on_5M_full_pretrained_best_epoch_f1 | null | [
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| amazon\_helpfulness\_classification\_on\_5M\_full\_pretrained\_best\_epoch\_f1
==============================================================================
This model is a fine-tuned version of BigTMiami/amazon\_pretraining\_5M\_model\_corrected on an unknown dataset.
It achieves the following results on the evalua... | [
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fill-mask | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# rubert-tiny2-finetuned-fintech
This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegr... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["generator"], "base_model": "cointegrated/rubert-tiny2", "model-index": [{"name": "rubert-tiny2-finetuned-fintech", "results": []}]} | Pastushoc/rubert-tiny2-finetuned-fintech | null | [
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| rubert-tiny2-finetuned-fintech
==============================
This model is a fine-tuned version of cointegrated/rubert-tiny2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 5.3573
Model description
-----------------
More information needed
Intended uses & limitation... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
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text-to-audio | transformers | # Tango 2: Aligning Diffusion-based Text-to-Audio Generative Models through Direct Preference Optimization
🎵 We developed **Tango 2** building upon **Tango** for text-to-audio generation. Tango 2 was initialized with the Tango-full-ft checkpoint and underwent alignment training using DPO on audio-alpaca, a pairwise t... | {"language": ["en"], "license": "cc-by-nc-sa-4.0", "tags": ["text-to-audio"], "datasets": ["bjoernp/AudioCaps", "declare-lab/audio_alpaca"], "pipeline_tag": "text-to-audio"} | declare-lab/tango2 | null | [
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| # Tango 2: Aligning Diffusion-based Text-to-Audio Generative Models through Direct Preference Optimization
We developed Tango 2 building upon Tango for text-to-audio generation. Tango 2 was initialized with the Tango-full-ft checkpoint and underwent alignment training using DPO on audio-alpaca, a pairwise text-to-aud... | [
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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": []} | cilantro9246/8tyttyi | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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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": []} | Serj/intent-classifier-flan-t5-small | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | adapter-transformers |
# Adapter `BigTMiami/F_adapter_ia3_classification_C_30` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head for classification.
Th... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/F_adapter_ia3_classification_C_30 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_helpfulness",
"region:us"
] | null | 2024-04-13T12:32:30+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/F_adapter_ia3_classification_C_30' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usage
First, install 'ada... | [
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text-generation | gguf |
## About
static quantize of https://huggingface.co/Vezora/Mistral-22B-v0.2
iQ Quants can be found here(Richard Erkhov's work): https://huggingface.co/RichardErkhov/Vezora_-_Mistral-22B-v0.2-gguf
## Provided Quants
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- ... | {"license": "apache-2.0", "library_name": "gguf", "pipeline_tag": "text-generation", "base_model": "Vezora/Mistral-22B-v0.2"} | NLPark/Mistral-22B-v0.2-GGUF | null | [
"gguf",
"text-generation",
"base_model:Vezora/Mistral-22B-v0.2",
"license:apache-2.0",
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] | null | 2024-04-13T12:34:47+00:00 | [] | [] | TAGS
#gguf #text-generation #base_model-Vezora/Mistral-22B-v0.2 #license-apache-2.0 #region-us
| About
-----
static quantize of URL
iQ Quants can be found here(Richard Erkhov's work): URL
Provided Quants
---------------
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image-segmentation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# segformer-b2-seed63-apr-13-v1
This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the... | {"license": "other", "tags": ["vision", "image-segmentation", "generated_from_trainer"], "base_model": "nvidia/mit-b3", "model-index": [{"name": "segformer-b2-seed63-apr-13-v1", "results": []}]} | unreal-hug/segformer-b2-seed63-apr-13-v1 | null | [
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| segformer-b2-seed63-apr-13-v1
=============================
This model is a fine-tuned version of nvidia/mit-b3 on the unreal-hug/REAL\_DATASET\_SEG\_401\_6\_lbls dataset.
It achieves the following results on the evaluation set:
* Loss: 1.7138
* Mean Iou: 0.1266
* Mean Accuracy: 0.2136
* Overall Accuracy: 0.4273
* ... | [
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unconditional-image-generation | diffusers |
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('way2mhemanth/sd-class-butte... | {"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]} | way2mhemanth/sd-class-butterflies-32 | null | [
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#diffusers #safetensors #pytorch #unconditional-image-generation #diffusion-models-class #license-mit #diffusers-DDPMPipeline #region-us
|
# Model Card for Unit 1 of the Diffusion Models Class
This model is a diffusion model for unconditional image generation of cute .
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] |
null | adapter-transformers |
# Adapter `BigTMiami/G_adapter_compactor_classification_C_30` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head for classificatio... | {"tags": ["adapter-transformers", "roberta"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/G_adapter_compactor_classification_C_30 | null | [
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"roberta",
"dataset:BigTMiami/amazon_helpfulness",
"region:us"
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#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/G_adapter_compactor_classification_C_30' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usage
First, instal... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **BlackJack-v1**
This is a trained model of a **Q-Learning** agent playing **BlackJack-v1** .
## Usage
```python
model = load_from_hub(repo_id="nzdb70/BlackJack-v1", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=... | {"tags": ["BlackJack-v1", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "BlackJack-v1", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BlackJack-v1", "type": "BlackJack-v1"}, "metrics": [{"type": "mean_reward",... | nzdb70/BlackJack-v1 | null | [
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#BlackJack-v1 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 BlackJack-v1
This is a trained model of a Q-Learning agent playing BlackJack-v1 .
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="ProrabVasili/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additiona... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | ProrabVasili/q-FrozenLake-v1-4x4-noSlippery | null | [
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#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
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object-detection | 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. -->
# detr_v1_50
This model is a fine-tuned version of [ssamperr/results_hugging_face](https://huggingface.co/ssamperr/results_hugging... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "ssamperr/results_hugging_face", "model-index": [{"name": "detr_v1_50", "results": []}]} | ssamperr/detr_v1_50 | null | [
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|
# detr_v1_50
This model is a fine-tuned version of ssamperr/results_hugging_face on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters... | [
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null | transformers |
# Uploaded model
- **Developed by:** lightontech
- **License:** apache-2.0
- **Finetuned from model :** SeaLLMs/SeaLLM-7B-v2
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/unsloth/ma... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "SeaLLMs/SeaLLM-7B-v2"} | lightontech/seallm-reviews | null | [
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# Uploaded model
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- License: apache-2.0
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This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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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": ["unsloth", "trl", "sft"]} | thinhle/seallm-reviews | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Lodo97/Test1 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# deep-wizard-7B-slerp
deep-wizard-7B-slerp is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [deepseek-ai/deepseek-math-7b-rl](https://huggingface.co/deepseek-ai/deepseek-math-7b-rl)
* [deepseek-ai/deepseek-math-7b-instruct](https://huggingface.co/deepseek-ai/deepseek-math-7b-... | {"license": "other", "tags": ["merge", "mergekit", "lazymergekit", "deepseek-ai/deepseek-math-7b-rl", "deepseek-ai/deepseek-math-7b-instruct"]} | Eliorkalfon/deep-wizard-7B-slerp | null | [
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|
# deep-wizard-7B-slerp
deep-wizard-7B-slerp is a merge of the following models using mergekit:
* deepseek-ai/deepseek-math-7b-rl
* deepseek-ai/deepseek-math-7b-instruct
## Configuration
| [
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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. -->
# results4
This model is a fine-tuned version of [jkhan447/sarcasm-detection-Bert-base-uncased-POS](https://huggingface.co/jkhan44... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "jkhan447/sarcasm-detection-Bert-base-uncased-POS", "model-index": [{"name": "results4", "results": []}]} | dianamihalache27/results4 | null | [
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|
# results4
This model is a fine-tuned version of jkhan447/sarcasm-detection-Bert-base-uncased-POS on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6646
- Accuracy: 0.7032
- F1: 0.3681
## Model description
More information needed
## Intended uses & limitations
More inform... | [
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null | transformers | ## About
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static quants of https://huggingface.co/ibivibiv/aegolius-acadicus-v1-30b
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/aegoliu... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "tags": ["moe", "moerge"], "base_model": "ibivibiv/aegolius-acadicus-v1-30b", "quantized_by": "mradermacher"} | mradermacher/aegolius-acadicus-v1-30b-GGUF | null | [
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-----
static quants of URL
weighted/imatrix quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
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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-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... | mikarn/distilbert-base-uncased-finetuned-emotion | null | [
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| 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: 0.1686
* Accuracy: 0.942
* F1: 0.9421
Model description
-----------------
Mor... | [
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text-generation | transformers |
LLaMA-13B converted to work with Transformers/HuggingFace. This is under a special license, please see the LICENSE file for details.
--
license: other
---
# LLaMA Model Card
## Model details
**Organization developing the model**
The FAIR team of Meta AI.
**Model date**
LLaMA was trained between December. 2022 and F... | {"license": "other"} | JG22/decapoda-research-llama-13b | null | [
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"text-generation",
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] | null | 2024-04-13T12:58:35+00:00 | [] | [] | TAGS
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| LLaMA-13B converted to work with Transformers/HuggingFace. This is under a special license, please see the LICENSE file for details.
--
license: other
-----------------
LLaMA Model Card
================
Model details
-------------
Organization developing the model
The FAIR team of Meta AI.
Model date
LLaMA wa... | [] | [
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