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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": []} | devesh220897/financial-chatbot-for-young-adults-4 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_splice_reconstructed-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_4096_512_46M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_splice\_reconstructed-seqsight\_4096\_512\_46M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
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*... | [
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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": []} | rPucs/gemma-7b-itTripletDolly-WebNLG | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# 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": []} | jsingh/autoflow-math-v0.3 | 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 | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_splice_reconstructed-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_4096_512_46M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_splice\_reconstructed-seqsight\_4096\_512\_46M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
*... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_splice_reconstructed-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_4096_512_46M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_splice\_reconstructed-seqsight\_4096\_512\_46M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation set:
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_0-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_0-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_4096_512_46M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_0-seqsight\_4096\_512\_46M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3687
* F1 Score: 0.8338
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_0-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_0-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_4096_512_46M-L8_f | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_0-seqsight\_4096\_512\_46M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3756
* F1 Score: 0.8367
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llava-1.5-7b-hf-ft-mix-vsft
This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/lla... | {"library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "llava-hf/llava-1.5-7b-hf", "model-index": [{"name": "llava-1.5-7b-hf-ft-mix-vsft", "results": []}]} | Salmoli/llava-1.5-7b-hf-ft-mix-vsft | null | [
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] | null | 2024-04-27T00:38:53+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-llava-hf/llava-1.5-7b-hf #region-us
|
# llava-1.5-7b-hf-ft-mix-vsft
This model is a fine-tuned version of llava-hf/llava-1.5-7b-hf on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training h... | [
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"## Intended uses & limitations\n\nMore information needed",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_0-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_0-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_4096_512_46M-L32_f | null | [
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"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_0-seqsight\_4096\_512\_46M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3707
* F1 Score: 0.8345
* Accuracy: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_1-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_1-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_4096_512_46M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T00:41:08+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_1-seqsight\_4096\_512\_46M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3440
* F1 Score: 0.8597
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | null | sailboat | {"license": "apache-2.0"} | ikukou/sailboat | null | [
"license:apache-2.0",
"region:us"
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#license-apache-2.0 #region-us
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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. -->
# Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224_fold5
This model is a fine-tuned version of [microsoft/swin-large-patch... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swin-large-patch4-window7-224", "model-index": [{"name": "Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224_fold5", "results": [{"task": {"type": "image-classification", "n... | onizukal/Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224_fold5 | null | [
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] | null | 2024-04-27T00:44:34+00:00 | [] | [] | TAGS
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| Boya1\_RMSProp\_1-e5\_10Epoch\_swin-large-patch4-window7-224\_fold5
===================================================================
This model is a fine-tuned version of microsoft/swin-large-patch4-window7-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1456
* ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_SPOAL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_SPOAL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_SPOAL_v1 | null | [
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T00:45:10+00:00 | [] | [] | TAGS
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|
# CS505_COQE_viT5_train_Instruction0_SPOAL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# CS505_COQE_viT5_train_Instruction0_SPOAL_v1\n\nThis model is a fine-tuned version of VietAI/vit5-large on the None dataset.",
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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## T... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_1-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_1-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_4096_512_46M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T00:48:37+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_1-seqsight\_4096\_512\_46M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3395
* F1 Score: 0.8587
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_1-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_1-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_4096_512_46M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T00:48:37+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_1-seqsight\_4096\_512\_46M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3578
* F1 Score: 0.8591
* Accuracy: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_4-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_4-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_4096_512_46M-L1_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T00:54:41+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_4-seqsight\_4096\_512\_46M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3559
* F1 Score: 0.8462
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_4-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_4-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_4096_512_46M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T00:54:42+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_4-seqsight\_4096\_512\_46M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3872
* F1 Score: 0.8608
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_OPSAL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_OPSAL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_OPSAL_v1 | null | [
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"endpoints_compatible",
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"region:us"
] | null | 2024-04-27T00:56:55+00:00 | [] | [] | TAGS
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|
# CS505_COQE_viT5_train_Instruction0_OPSAL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# CS505_COQE_viT5_train_Instruction0_OPSAL_v1\n\nThis model is a fine-tuned version of VietAI/vit5-large on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## T... | [
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text-generation | transformers |
# Model
This model is fine-tuned based on Meta-Llama/Meta-Llama-3-8B instructions via mlx-lm.
**Note:** The glaive-function-calling-v2 dataset contains some invalid JSON and single quotes for the arguments' values. I have re-trained the model based on cleaned-up data. If you encounter issues with the function callin... | {"language": ["en"], "license": "llama3", "datasets": ["mzbac/glaive-function-calling-v2-llama-3-format"]} | mzbac/llama-3-8B-Instruct-function-calling | null | [
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|
# Model
This model is fine-tuned based on Meta-Llama/Meta-Llama-3-8B instructions via mlx-lm.
Note: The glaive-function-calling-v2 dataset contains some invalid JSON and single quotes for the arguments' values. I have re-trained the model based on cleaned-up data. If you encounter issues with the function calling JS... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_PASOL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_PASOL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_PASOL_v1 | null | [
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"region:us"
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|
# CS505_COQE_viT5_train_Instruction0_PASOL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_APSOL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_APSOL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_APSOL_v1 | null | [
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|
# CS505_COQE_viT5_train_Instruction0_APSOL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
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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": []} | leminhnhat/bug-impact-level-falcon-7b | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
<!-- 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. -->
# 0.001_4iters_bs128_nodpo_only4w_userresponse_iter_4
This model is a fine-tuned version of [ShenaoZhang/0.001_4iters_bs128_nodpo_... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_userresponse_iter_3", "model-index": [{"name": "0.001_4iters_bs128_nodpo_only4w_userresponse_... | ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_userresponse_iter_4 | null | [
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"autotrain_compat... | null | 2024-04-27T01:01:16+00:00 | [] | [] | TAGS
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# 0.001_4iters_bs128_nodpo_only4w_userresponse_iter_4
This model is a fine-tuned version of ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_userresponse_iter_3 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training a... | [
"# 0.001_4iters_bs128_nodpo_only4w_userresponse_iter_4\n\nThis model is a fine-tuned version of ShenaoZhang/0.001_4iters_bs128_nodpo_only4w_userresponse_iter_3 on the updated and the original datasets.",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_4-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_4-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_4096_512_46M-L32_f | null | [
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| GUE\_tf\_4-seqsight\_4096\_512\_46M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5633
* F1 Score: 0.8590
* Accuracy: 0... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_3-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_3-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_4096_512_46M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_3-seqsight\_4096\_512\_46M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5315
* F1 Score: 0.7102
* Accuracy: 0.7... | [
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text-generation | transformers |
# Model Card for johnsnowlabs/JSL-MedLlama-3-70B-v2.0
[<img src="https://repository-images.githubusercontent.com/104670986/2e728700-ace4-11ea-9cfc-f3e060b25ddf">](http://www.johnsnowlabs.com)
This model is developed by [John Snow Labs](https://www.johnsnowlabs.com/).
This model is trained on medical datasets to pro... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["medical"]} | johnsnowlabs/JSL-MedLlama-3-70B-v2.0 | null | [
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| Model Card for johnsnowlabs/JSL-MedLlama-3-70B-v2.0
===================================================
<img src="URL
This model is developed by John Snow Labs.
This model is trained on medical datasets to provide state-of-the-art performance on biomedical benchmarks: Open Medical LLM Leaderboard.
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null | null |
# MeliodasExperiment26-7B
MeliodasExperiment26-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: AurelPx/Meliodas-7b-dare
- model: yam-peleg/Experiment26-7B
me... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/MeliodasExperiment26-7B | null | [
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#merge #mergekit #lazymergekit #automerger #license-apache-2.0 #region-us
|
# MeliodasExperiment26-7B
MeliodasExperiment26-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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text-generation | transformers |
<div align="center">
<img width="260px" src="https://cdn-uploads.huggingface.co/production/uploads/5f3fe13d79c1ba4c353d0c19/BrQCb95lmEIFz79QAmoNA.png"></div>
<div align="center">
<h1>Advanc... | {"language": ["en"], "license": "llama3", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "widget": [{"example_title": "OpenBioLLM-70B", "messages": [{"role": "system", "content": "You are an expert a... | LoneStriker/OpenBioLLM-Llama3-70B-2.4bpw-h6-exl2 | null | [
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Advancing Open-source Large Language Models in Medical Domain
=============================================================
Online Demo
|
GitHub
|
[](#) |
Discord
!image/jpeg
Introducing OpenBioLLM-70B: A State-of-the-Art Open Source Biomedical Larg... | [] | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_3-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_3-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_4096_512_46M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:09:05+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_3-seqsight\_4096\_512\_46M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5223
* F1 Score: 0.7373
* Accuracy: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_3-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_3-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_4096_512_46M-L8_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:09:05+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_3-seqsight\_4096\_512\_46M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5282
* F1 Score: 0.7300
* Accuracy: 0.7... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text-generation | transformers |
<!-- 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. -->
# 0.001_4iters_bs256_nodpo_only4w_userresponse_iter_4
This model is a fine-tuned version of [ShenaoZhang/0.001_4iters_bs256_nodpo_... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.001_4iters_bs256_nodpo_only4w_userresponse_iter_3", "model-index": [{"name": "0.001_4iters_bs256_nodpo_only4w_userresponse_... | ShenaoZhang/0.001_4iters_bs256_nodpo_only4w_userresponse_iter_4 | null | [
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"license:mit",
"autotrain_compat... | null | 2024-04-27T01:10:49+00:00 | [] | [] | TAGS
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# 0.001_4iters_bs256_nodpo_only4w_userresponse_iter_4
This model is a fine-tuned version of ShenaoZhang/0.001_4iters_bs256_nodpo_only4w_userresponse_iter_3 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training a... | [
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"## Model description\n\nMore information needed",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_2-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_2-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_4096_512_46M-L1_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:12:28+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_2-seqsight\_4096\_512\_46M-L1\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4291
* F1 Score: 0.7986
* Accuracy: 0.7... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | transformers |
# Uploaded model
- **Developed by:** berger815
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "gguf"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | berger815/sail | null | [
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"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-27T01:14:05+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #llama #text-generation-inference #unsloth #en #base_model-unsloth/llama-3-8b-bnb-4bit #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: berger815
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_2-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_2-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_4096_512_46M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:16:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_2-seqsight\_4096\_512\_46M-L8\_f
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4177
* F1 Score: 0.8059
* Accuracy: 0.8... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_2-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_tf_2-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_4096_512_46M-L32_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:16:37+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_tf\_2-seqsight\_4096\_512\_46M-L32\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4244
* F1 Score: 0.8144
* Accuracy: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_virus_covid-seqsight_4096_512_46M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_virus_covid-seqsight_4096_512_46M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_4096_512_46M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:17:02+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_virus\_covid-seqsight\_4096\_512\_46M-L1\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4763
* F1 Score: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_virus_covid-seqsight_4096_512_46M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_virus_covid-seqsight_4096_512_46M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_4096_512_46M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:17:17+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_virus\_covid-seqsight\_4096\_512\_46M-L8\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1081
* F1 Score: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_SPAOL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_SPAOL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_SPAOL_v1 | null | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:VietAI/vit5-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T01:17:27+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-VietAI/vit5-large #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# CS505_COQE_viT5_train_Instruction0_SPAOL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# CS505_COQE_viT5_train_Instruction0_SPAOL_v1\n\nThis model is a fine-tuned version of VietAI/vit5-large on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## T... | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-VietAI/vit5-large #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# CS505_COQE_viT5_train_Instruction0_SPAOL_v1\n\nThis model is a fine-tuned version of... | [
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text-generation | transformers |
<div align="center">
<img width="260px" src="https://cdn-uploads.huggingface.co/production/uploads/5f3fe13d79c1ba4c353d0c19/BrQCb95lmEIFz79QAmoNA.png"></div>
<div align="center">
<h1>Advanc... | {"language": ["en"], "license": "llama3", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "widget": [{"example_title": "OpenBioLLM-70B", "messages": [{"role": "system", "content": "You are an expert a... | LoneStriker/OpenBioLLM-Llama3-70B-3.5bpw-h6-exl2 | null | [
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"arxiv:2212.13138",
"arxiv:2305.09617",
"arxiv:2402.07023",
"b... | null | 2024-04-27T01:18:25+00:00 | [
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Advancing Open-source Large Language Models in Medical Domain
=============================================================
Online Demo
|
GitHub
|
[](#) |
Discord
!image/jpeg
Introducing OpenBioLLM-70B: A State-of-the-Art Open Source Biomedical Larg... | [] | [
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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. -->
# llama2-envi-tran-10000
This model is a fine-tuned version of [unsloth/llama-2-7b-bnb-4bit](https://huggingface.co/unsloth/llama-... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "unsloth", "generated_from_trainer"], "base_model": "unsloth/llama-2-7b-bnb-4bit", "model-index": [{"name": "llama2-envi-tran-10000", "results": []}]} | mob2711/llama2-envi-tran-10000 | null | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"unsloth",
"generated_from_trainer",
"base_model:unsloth/llama-2-7b-bnb-4bit",
"license:apache-2.0",
"region:us"
] | null | 2024-04-27T01:22:19+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #unsloth #generated_from_trainer #base_model-unsloth/llama-2-7b-bnb-4bit #license-apache-2.0 #region-us
| llama2-envi-tran-10000
======================
This model is a fine-tuned version of unsloth/llama-2-7b-bnb-4bit on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0906
Model description
-----------------
More information needed
Intended uses & limitations
-----------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 4\n* seed: 3407\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 8\n* eva... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_virus_covid-seqsight_4096_512_46M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_46M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_46M", "model-index": [{"name": "GUE_virus_covid-seqsight_4096_512_46M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_4096_512_46M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_46M",
"region:us"
] | null | 2024-04-27T01:23:35+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_46M #region-us
| GUE\_virus\_covid-seqsight\_4096\_512\_46M-L32\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_46M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9287
* F1 Score:... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_tata-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_8192_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T01:23:36+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_8192\_512\_30M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_tata-seqsight_8192_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_8192_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_8192_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T01:26:35+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_8192\_512\_30M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_OPASL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_OPASL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_OPASL_v1 | null | [
"transformers",
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"safetensors",
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"base_model:VietAI/vit5-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T01:29:08+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-VietAI/vit5-large #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# CS505_COQE_viT5_train_Instruction0_OPASL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# CS505_COQE_viT5_train_Instruction0_OPASL_v1\n\nThis model is a fine-tuned version of VietAI/vit5-large on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## T... | [
"TAGS\n#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-VietAI/vit5-large #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_tata-seqsight_8192_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_8192_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_8192_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T01:30:04+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_8192\_512\_30M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_notata-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_8192_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T01:30:18+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_8192\_512\_30M-L1\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation se... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text-generation | transformers |
<div align="center">
<img width="260px" src="https://cdn-uploads.huggingface.co/production/uploads/5f3fe13d79c1ba4c353d0c19/BrQCb95lmEIFz79QAmoNA.png"></div>
<div align="center">
<h1>Advanc... | {"language": ["en"], "license": "llama3", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "widget": [{"example_title": "OpenBioLLM-70B", "messages": [{"role": "system", "content": "You are an expert a... | LoneStriker/OpenBioLLM-Llama3-70B-4.0bpw-h6-exl2 | null | [
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Advancing Open-source Large Language Models in Medical Domain
=============================================================
Online Demo
|
GitHub
|
[](#) |
Discord
!image/jpeg
Introducing OpenBioLLM-70B: A State-of-the-Art Open Source Biomedical Larg... | [] | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_PAOSL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_PAOSL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_PAOSL_v1 | null | [
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|
# CS505_COQE_viT5_train_Instruction0_PAOSL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
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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. -->
# model_3
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown datase... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-uncased", "model-index": [{"name": "model_3", "results": []}]} | beloiual/model_3 | null | [
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|
# model_3
This model is a fine-tuned version of bert-base-uncased 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 followi... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CS505_COQE_viT5_train_Instruction0_APOSL_v1
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/Vie... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "VietAI/vit5-large", "model-index": [{"name": "CS505_COQE_viT5_train_Instruction0_APOSL_v1", "results": []}]} | ThuyNT/CS505_COQE_viT5_train_Instruction0_APOSL_v1 | null | [
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|
# CS505_COQE_viT5_train_Instruction0_APOSL_v1
This model is a fine-tuned version of VietAI/vit5-large on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Tra... | [
"# CS505_COQE_viT5_train_Instruction0_APOSL_v1\n\nThis model is a fine-tuned version of VietAI/vit5-large on the None dataset.",
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"## Training and evaluation data\n\nMore information needed",
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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. -->
# model_3_edges
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/disti... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "model_3_edges", "results": []}]} | beloiual/model_3_edges | null | [
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|
# model_3_edges
This model is a fine-tuned version of distilbert/distilbert-base-uncased 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 hyper... | [
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text-generation | transformers |
# Model Card for Model ID
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text-generation | transformers | Hello, my name is nanit. I am an AI assistant designed to help you with various tasks and provide information. I can assist with answering questions, providing recommendations, and performing calculations. I am constantly learning and improving to better serve you. If you have any specific questions or tasks you would ... | {"license": "other", "library_name": "transformers"} | AlanRobotics/nanit_slerp | null | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_notata-seqsight_8192_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_8192_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_8192_512_30M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_8192\_512\_30M-L8\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
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text-generation | transformers |
<div align="center">
<img width="260px" src="https://cdn-uploads.huggingface.co/production/uploads/5f3fe13d79c1ba4c353d0c19/BrQCb95lmEIFz79QAmoNA.png"></div>
<div align="center">
<h1>Advanc... | {"language": ["en"], "license": "llama3", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "widget": [{"example_title": "OpenBioLLM-70B", "messages": [{"role": "system", "content": "You are an expert a... | LoneStriker/OpenBioLLM-Llama3-70B-4.65bpw-h6-exl2 | null | [
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Advancing Open-source Large Language Models in Medical Domain
=============================================================
Online Demo
|
GitHub
|
[](#) |
Discord
!image/jpeg
Introducing OpenBioLLM-70B: A State-of-the-Art Open Source Biomedical Larg... | [] | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_notata-seqsight_8192_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_8192_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_8192_512_30M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_8192\_512\_30M-L32\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation ... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_all-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_8192_512_30M-L1_f | null | [
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| GUE\_prom\_prom\_core\_all-seqsight\_8192\_512\_30M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_all-seqsight_8192_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_8192_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_8192_512_30M-L8_f | null | [
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=========================================================
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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. -->
# model_3_edges
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/disti... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "model_3_edges", "results": []}]} | anirudhramoo/model_3_edges | null | [
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|
# model_3_edges
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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text-generation | transformers |
# Model Card for Model ID
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text-generation | transformers |
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text-generation | transformers |
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text-generation | transformers |
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text-generation | transformers | # Description
4-bit AWQ-quantized version of [stylellm/HongLouMeng-6b](https://huggingface.co/stylellm/HongLouMeng-6b)
| {"license": "other", "license_name": "yi-license", "license_link": "https://huggingface.co/01-ai/Yi-6B/blob/main/LICENSE"} | stylellm/HongLouMeng-6b-AWQ | null | [
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#transformers #safetensors #llama #text-generation #conversational #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| # Description
4-bit AWQ-quantized version of stylellm/HongLouMeng-6b
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/aaditya/OpenBioLLM-Llama3-70B
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/OpenBioLLM-... | {"language": ["en"], "license": "llama3", "library_name": "transformers", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "aaditya/OpenBioLLM-Llama3-70B", "quantized_by": "mradermacher"} | mradermacher/OpenBioLLM-Llama3-70B-i1-GGUF | null | [
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| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_all-seqsight_8192_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_8192_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_8192_512_30M-L32_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_8192\_512\_30M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation set:
... | [
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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. -->
# 0.001_4iters_bs256_nodpo_only4w_iter_3
This model is a fine-tuned version of [ShenaoZhang/0.001_4iters_bs256_nodpo_only4w_iter_2... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZhang/0.001_4iters_bs256_nodpo_only4w_iter_2", "model-index": [{"name": "0.001_4iters_bs256_nodpo_only4w_iter_3", "results": []}]} | ShenaoZhang/0.001_4iters_bs256_nodpo_only4w_iter_3 | null | [
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# 0.001_4iters_bs256_nodpo_only4w_iter_3
This model is a fine-tuned version of ShenaoZhang/0.001_4iters_bs256_nodpo_only4w_iter_2 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More i... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_notata-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_8192_512_30M-L1_f | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_core\_notata-seqsight\_8192\_512\_30M-L1\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evaluation... | [
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text-generation | transformers | # EinsteinBagel-8B (Einstein V6.1 & Bagel V1.0)
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
The purpose of this experiment was to combine the maximum amount of finetuned datasets possible for the Llama 3 8B architecture.
## Merge Details
### Merge Metho... | {"license": "llama3", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Weyaxi/Einstein-v6.1-Llama3-8B", "meta-llama/Meta-Llama-3-8B", "jondurbin/bagel-8b-v1.0"]} | TitleOS/EinsteinBagel-8B | null | [
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... | null | 2024-04-27T02:04:04+00:00 | [
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| # EinsteinBagel-8B (Einstein V6.1 & Bagel V1.0)
This is a merge of pre-trained language models created using mergekit.
The purpose of this experiment was to combine the maximum amount of finetuned datasets possible for the Llama 3 8B architecture.
## Merge Details
### Merge Method
This model was merged using the Mo... | [
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text-generation | transformers |
<div align="center">
<img width="260px" src="https://cdn-uploads.huggingface.co/production/uploads/5f3fe13d79c1ba4c353d0c19/BrQCb95lmEIFz79QAmoNA.png"></div>
<div align="center">
<h1>Advanc... | {"language": ["en"], "license": "llama3", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "widget": [{"example_title": "OpenBioLLM-70B", "messages": [{"role": "system", "content": "You are an expert a... | LoneStriker/OpenBioLLM-Llama3-70B-5.0bpw-h6-exl2 | null | [
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Advancing Open-source Large Language Models in Medical Domain
=============================================================
Online Demo
|
GitHub
|
[](#) |
Discord
!image/jpeg
Introducing OpenBioLLM-70B: A State-of-the-Art Open Source Biomedical Larg... | [] | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_notata-seqsight_8192_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_8192_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_8192_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T02:09:28+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_core\_notata-seqsight\_8192\_512\_30M-L8\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evaluation... | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_doub... | {"library_name": "peft"} | vicaloy/llama-2-13-b-chat-hf-checkpoints | null | [
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#peft #region-us
| ## Training procedure
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- load_in_4bit: True
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- bnb_4bit_quant_type: nf4
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_notata-seqsight_8192_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_8192_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_8192_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_core\_notata-seqsight\_8192\_512\_30M-L32\_f
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evaluati... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text-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. -->
# my_awesome_model
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "my_awesome_model", "results": []}]} | brunhild217/my_awesome_model | null | [
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| my\_awesome\_model
==================
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1924
* Accuracy: 0.9529
Model description
-----------------
More information needed
Intended uses & limitations
-------------------... | [
"### 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=(0.9,0.999) 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. -->
# GUE_prom_prom_core_tata-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_8192_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_8192\_512\_30M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluation set:
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_tata-seqsight_8192_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_8192_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_8192_512_30M-L8_f | null | [
"peft",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_8192\_512\_30M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluation set:
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "datasets": ["thesven/pihkal-tihkal-orpo-dpo-dataset"]} | thesven/thesven-Tihkal-Pihkal-ORPO-Llama-3-8B-bnb-4bit | 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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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. -->
# lmd-4bars-2048-epochs10
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
## Mod... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "gpt2", "model-index": [{"name": "lmd-4bars-2048-epochs10", "results": []}]} | MikeMpapa/lmd-4bars-2048-epochs10 | null | [
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#transformers #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #base_model-gpt2 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# lmd-4bars-2048-epochs10
This model is a fine-tuned version of gpt2 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The foll... | [
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text-to-image | null |
gguf quantized version of https://huggingface.co/stabilityai/sdxl-turbo | {"license": "other", "license_name": "sai-nc-community", "license_link": "https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.TXT", "pipeline_tag": "text-to-image"} | OlegSkutte/sdxl-turbo-GGUF | null | [
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"text-to-image",
"license:other",
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#gguf #text-to-image #license-other #region-us
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_tata-seqsight_8192_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_8192_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_8192_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T02:18:53+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_8192\_512\_30M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluation set... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_all-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M]... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_8192_512_30M-L1_f | null | [
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"safetensors",
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"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_8192\_512\_30M-L1\_f
========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all dataset.
It achieves the following results on the evaluation set:
* Lo... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_all-seqsight_8192_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M]... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_8192_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_8192_512_30M-L8_f | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_8192\_512\_30M-L8\_f
========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all dataset.
It achieves the following results on the evaluation set:
* Lo... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_all-seqsight_8192_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_8192_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_8192_512_30M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_8192\_512\_30M-L32\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all dataset.
It achieves the following results on the evaluation set:
* ... | [
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text-generation | transformers |
<div align="center">
<img width="260px" src="https://cdn-uploads.huggingface.co/production/uploads/5f3fe13d79c1ba4c353d0c19/BrQCb95lmEIFz79QAmoNA.png"></div>
<div align="center">
<h1>Advanc... | {"language": ["en"], "license": "llama3", "tags": ["llama-3", "llama", "Mixtral", "instruct", "finetune", "chatml", "DPO", "RLHF", "gpt4", "distillation"], "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "widget": [{"example_title": "OpenBioLLM-70B", "messages": [{"role": "system", "content": "You are an expert a... | LoneStriker/OpenBioLLM-Llama3-70B-6.0bpw-h6-exl2 | null | [
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Advancing Open-source Large Language Models in Medical Domain
=============================================================
Online Demo
|
GitHub
|
[](#) |
Discord
!image/jpeg
Introducing OpenBioLLM-70B: A State-of-the-Art Open Source Biomedical Larg... | [] | [
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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": []} | azferruolo/llamacheck | null | [
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
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text-generation | transformers |
# miqu-evil-dpo
# **Model Details**
## Description
miqu-evil-dpo is fine-tuned model based on miqu, serving as a direct successor to PiVoT-0.1-Evil-a.
It is trained with evil-tune method applied.
<!-- prompt-template start -->
## Prompt template: Mistral Inst
```
<s> [INST] {inst} [... | {"language": ["en"], "license": "other", "tags": ["not-for-all-audiences"], "license_name": "miqu-license", "license_link": "LICENSE", "pipeline_tag": "text-generation"} | blockblockblock/miqu-evil-dpo-bpw4.6-exl2 | null | [
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|
# miqu-evil-dpo
# Model Details
## Description
miqu-evil-dpo is fine-tuned model based on miqu, serving as a direct successor to PiVoT-0.1-Evil-a.
It is trained with evil-tune method applied.
!image/png
## Prompt template: Mistral Inst
## Disclaimer
The AI model provided herein is intended for experimental... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K14ac-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_8192_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_8192\_512\_30M-L1\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4945
* F1 Score: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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text-generation | transformers | # Medwest
Just testing my method task_swapping.
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 task_swapping merge method using [internistai/base-7b-v0.2](https://huggingface.co/internistai/b... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["senseable/WestLake-7B-v2", "internistai/base-7b-v0.2"]} | Aryanne/MedWest-7B | null | [
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| # Medwest
Just testing my method task_swapping.
This is a merge of pre-trained language models created using mergekit.
## Merge Details
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This model was merged using the task_swapping merge method using internistai/base-7b-v0.2 as a base.
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_doub... | {"library_name": "peft"} | UsamaCoder/finetunedLlama-python-C | null | [
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#peft #pytorch #llama #region-us
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- load_in_4bit: True
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- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
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- bnb_4bit_quant_type: nf4
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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": []} | zandfj/LLaMA2-7B-Chat-dpo-f-042618_MIx | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-to-image | null |
gguf quantized version of https://huggingface.co/ByteDance/SDXL-Lightning | {"license": "openrail++", "pipeline_tag": "text-to-image"} | OlegSkutte/SDXL-Lightning-GGUF | null | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K14ac-seqsight_8192_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_8192_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_8192_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T02:44:04+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_8192\_512\_30M-L8\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4967
* F1 Score: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* o... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K14ac-seqsight_8192_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_8192_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_8192_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T02:45:47+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_8192\_512\_30M-L32\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4901
* F1 Score:... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* o... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimiz... |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me2-seqsight_8192_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_8192_512_30M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_8192_512_30M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_8192_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_8192_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_8192_512_30M",
"region:us"
] | null | 2024-04-27T02:46:12+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_8192\_512\_30M-L1\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_8192\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5958
* F1 Score: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* o... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_8192_512_30M #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimiz... |
text2text-generation | transformers |
### Using .generate()
```python
from transformers import GenerationConfig, T5ForConditionalGeneration, T5Tokenizer
model_name = "cu-kairos/propbank_srl_seq2seq_t5_small"
model = T5ForConditionalGeneration.from_pretrained(model_name)
tokenizer = T5Tokenizer.from_pretrained(model_name)
generation_config = GenerationCo... | {"license": "apache-2.0"} | cu-kairos/propbank_srl_seq2seq_t5_small | null | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-27T02:46:48+00:00 | [] | [] | TAGS
#transformers #safetensors #t5 #text2text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
### Using .generate()
### Using pipeline
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] |
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