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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_3-seqsight_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_mouse_3-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:19:38+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_3-seqsight\_32768\_512\_30M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9675
* F1 Score: 0.8158
* A... | [
"### 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_mouse_3-seqsight_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_mouse_3-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:20:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_3-seqsight\_32768\_512\_30M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1849
* F1 Score: 0.8326
*... | [
"### 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_mouse_2-seqsight_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_mouse_2-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:20:46+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_2-seqsight\_32768\_512\_30M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3390
* F1 Score: 0.8567
* A... | [
"### 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_mouse_2-seqsight_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_mouse_2-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:21:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_2-seqsight\_32768\_512\_30M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5822
* F1 Score: 0.8902
*... | [
"### 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_mouse_2-seqsight_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_mouse_2-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_32768_512_30M-L8_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:21:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_2-seqsight\_32768\_512\_30M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5138
* F1 Score: 0.8780
* A... | [
"### 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", "tags": []} | OwOOwO/finalnew | 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_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:23:32+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_splice\_reconstructed-seqsight\_32768\_512\_30M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed 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_splice_reconstructed-seqsight_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_32768_512_30M-L32_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
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] | null | 2024-04-30T05:23:45+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_splice\_reconstructed-seqsight\_32768\_512\_30M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed 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_splice_reconstructed-seqsight_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_32768_512_30M-L8_f | null | [
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"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:23:48+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_splice\_reconstructed-seqsight\_32768\_512\_30M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed 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_tf_0-seqsight_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_0-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
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"region:us"
] | null | 2024-04-30T05:24:15+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_0-seqsight\_32768\_512\_30M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3736
* F1 Score: 0.8334
* Accuracy: ... | [
"### 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_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_0-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:24:21+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_0-seqsight\_32768\_512\_30M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3679
* F1 Score: 0.8303
* Accuracy: ... | [
"### 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_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_0-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:25:20+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_0-seqsight\_32768\_512\_30M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3740
* F1 Score: 0.8210
* Accuracy... | [
"### 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_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_1-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:25:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_1-seqsight\_32768\_512\_30M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3438
* F1 Score: 0.8568
* Accuracy: ... | [
"### 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_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_1-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:26:14+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_1-seqsight\_32768\_512\_30M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3377
* F1 Score: 0.8586
* Accuracy: ... | [
"### 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_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_1-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:26:31+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_1-seqsight\_32768\_512\_30M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3492
* F1 Score: 0.8434
* Accuracy... | [
"### 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_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_4-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:27:19+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_4-seqsight\_32768\_512\_30M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3600
* F1 Score: 0.8339
* Accuracy: ... | [
"### 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_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_4-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:27:19+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_4-seqsight\_32768\_512\_30M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3637
* F1 Score: 0.8357
* Accuracy: ... | [
"### 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 | # maverick_v2_folder
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 arithmetic](https://arxiv.org/abs/2212.04089) merge method using D:\Learning Centre\GenAI\LLM Leaderboard\2024042801... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": []} | shyamieee/Maverick-v2.0 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2212.04089",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-30T05:27:21+00:00 | [
"2212.04089"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #mergekit #merge #conversational #arxiv-2212.04089 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # maverick_v2_folder
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the task arithmetic merge method using D:\Learning Centre\GenAI\LLM Leaderboard\2024042801\mergekit-main\models\Mistral-7B-Instruct-v0.2 as a base.
### Models Mer... | [
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reinforcement-learning | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Docum... | {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | aw-infoprojekt/poca-SoccerTwos | null | [
"ml-agents",
"tensorboard",
"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] | null | 2024-04-30T05:27:53+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us
|
# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* ... | [
"# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short ... | [
"TAGS\n#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us \n",
"# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Doc... | [
39,
208
] | [
"TAGS\n#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us \n# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documenta... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Aryaman1/ppo-lunarlander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-30T05:28:56+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... | [
31,
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"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add your code"
] |
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_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_4-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:30:14+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_4-seqsight\_32768\_512\_30M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4127
* F1 Score: 0.8349
* Accuracy... | [
"### 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* ... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_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* optimi... |
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_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_3-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:30:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_3-seqsight\_32768\_512\_30M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5673
* F1 Score: 0.6979
* Accuracy: ... | [
"### 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_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_3-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:31:18+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_3-seqsight\_32768\_512\_30M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5599
* F1 Score: 0.6879
* Accuracy: ... | [
"### 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_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_3-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:31:34+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_3-seqsight\_32768\_512\_30M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5543
* F1 Score: 0.7095
* Accuracy... | [
"### 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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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_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* optimi... |
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. -->
# pegasus-samsum
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_da... | {"tags": ["generated_from_trainer"], "base_model": "google/pegasus-cnn_dailymail", "model-index": [{"name": "pegasus-samsum", "results": []}]} | OscarNav/pegasus-samsum | null | [
"transformers",
"pytorch",
"pegasus",
"text2text-generation",
"generated_from_trainer",
"base_model:google/pegasus-cnn_dailymail",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T05:32:13+00:00 | [] | [] | TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #base_model-google/pegasus-cnn_dailymail #autotrain_compatible #endpoints_compatible #region-us
| pegasus-samsum
==============
This model is a fine-tuned version of google/pegasus-cnn\_dailymail on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4900
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_2-seqsight_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_2-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:32:17+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_2-seqsight\_32768\_512\_30M-L1\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4629
* F1 Score: 0.7859
* Accuracy: ... | [
"### 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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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_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* optimi... |
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_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://hu... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_2-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:32:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_2-seqsight\_32768\_512\_30M-L8\_f
==========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4703
* F1 Score: 0.7919
* Accuracy: ... | [
"### 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 |
# 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": []} | pkarypis/codegen-53m-config | null | [
"transformers",
"codegen",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T05:32:56+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #codegen #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | 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_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https://h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_tf_2-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:33:17+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_tf\_2-seqsight\_32768\_512\_30M-L32\_f
===========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4705
* F1 Score: 0.7779
* Accuracy... | [
"### 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_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_virus_covid-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:33:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_virus\_covid-seqsight\_32768\_512\_30M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6920
* 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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unconditional-image-generation | diffusers |
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('fath2024/sd-class-butterfli... | {"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]} | fath2024/sd-class-butterflies-32 | null | [
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"safetensors",
"pytorch",
"unconditional-image-generation",
"diffusion-models-class",
"license:mit",
"diffusers:DDPMPipeline",
"region:us"
] | null | 2024-04-30T05:33:45+00:00 | [] | [] | TAGS
#diffusers #safetensors #pytorch #unconditional-image-generation #diffusion-models-class #license-mit #diffusers-DDPMPipeline #region-us
|
# Model Card for Unit 1 of the Diffusion Models Class
This model is a diffusion model for unconditional image generation of cute .
## Usage
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] |
null | null |
**You asked for it, you got it.**
Use ChatML.
Since MythoMax and Airoboros, models have been feeling... very robotic. Ironic huh? We supposedly have the best models yet all of them are completely... I can't really put it into words but they behave in a manner a child would behave if their parents slapped them whenev... | {"license": "llama3", "tags": ["not-for-all-audiences"]} | aaronday3/unhinged | null | [
"safetensors",
"not-for-all-audiences",
"license:llama3",
"region:us"
] | null | 2024-04-30T05:33:45+00:00 | [] | [] | TAGS
#safetensors #not-for-all-audiences #license-llama3 #region-us
|
You asked for it, you got it.
Use ChatML.
Since MythoMax and Airoboros, models have been feeling... very robotic. Ironic huh? We supposedly have the best models yet all of them are completely... I can't really put it into words but they behave in a manner a child would behave if their parents slapped them whenever t... | [] | [
"TAGS\n#safetensors #not-for-all-audiences #license-llama3 #region-us \n"
] | [
23
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"TAGS\n#safetensors #not-for-all-audiences #license-llama3 #region-us \n"
] |
reinforcement-learning | null |
# PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.
# Hyperparameters
| {"tags": ["LunarLander-v2", "ppo", "deep-reinforcement-learning", "reinforcement-learning", "custom-implementation", "deep-rl-course"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarLander-v2... | aw-infoprojekt/ppo-CartPole-v1-scratch | null | [
"tensorboard",
"LunarLander-v2",
"ppo",
"deep-reinforcement-learning",
"reinforcement-learning",
"custom-implementation",
"deep-rl-course",
"model-index",
"region:us"
] | null | 2024-04-30T05:36:04+00:00 | [] | [] | TAGS
#tensorboard #LunarLander-v2 #ppo #deep-reinforcement-learning #reinforcement-learning #custom-implementation #deep-rl-course #model-index #region-us
|
# PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.
# Hyperparameters
| [
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] |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-large-plm-nsp-10000
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an un... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "roberta-large", "model-index": [{"name": "roberta-large-plm-nsp-10000", "results": []}]} | mhr2004/roberta-large-plm-nsp-10000 | null | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:roberta-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T05:36:15+00:00 | [] | [] | TAGS
#transformers #safetensors #roberta #text-classification #generated_from_trainer #base_model-roberta-large #license-mit #autotrain_compatible #endpoints_compatible #region-us
| roberta-large-plm-nsp-10000
===========================
This model is a fine-tuned version of roberta-large on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6943
Model description
-----------------
More information needed
Intended uses & limitations
-------------------... | [
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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_32768_512_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_virus_covid-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:36:37+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_virus\_covid-seqsight\_32768\_512\_30M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3659
* 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_virus_covid-seqsight_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_virus_covid-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_virus_covid-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:37:28+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_virus\_covid-seqsight\_32768\_512\_30M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_virus\_covid dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1872
* F1 Sco... | [
"### 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_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_32768_512_43M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:37:39+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_32768\_512\_43M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_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_300_tata-seqsight_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_32768_512_43M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:38:12+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_32768\_512\_43M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
... | [
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text-generation | transformers |
# TooManyMix_LLM_02
TooManyMix_LLM_02 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [jdqwoi/TooManyMixed-LLM_04](https://huggingface.co/jdqwoi/TooManyMixed-LLM_04)
* [jdqwoi/TooManyMix_LLM_01](https://huggingface.co/jd... | {"tags": ["merge", "mergekit", "lazymergekit", "jdqwoi/TooManyMixed-LLM_04", "jdqwoi/TooManyMix_LLM_01", "unsloth"], "base_model": ["jdqwoi/TooManyMixed-LLM_04", "jdqwoi/TooManyMix_LLM_01"]} | jdqwoi/TooManyMix_LLM_02.gguf | null | [
"transformers",
"safetensors",
"gguf",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"jdqwoi/TooManyMixed-LLM_04",
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"unsloth",
"conversational",
"base_model:jdqwoi/TooManyMixed-LLM_04",
"base_model:jdqwoi/TooManyMix_LLM_01",
"autotrain_comp... | null | 2024-04-30T05:38:18+00:00 | [] | [] | TAGS
#transformers #safetensors #gguf #mistral #text-generation #merge #mergekit #lazymergekit #jdqwoi/TooManyMixed-LLM_04 #jdqwoi/TooManyMix_LLM_01 #unsloth #conversational #base_model-jdqwoi/TooManyMixed-LLM_04 #base_model-jdqwoi/TooManyMix_LLM_01 #autotrain_compatible #endpoints_compatible #text-generation-inference... |
# TooManyMix_LLM_02
TooManyMix_LLM_02 is a merge of the following models using LazyMergekit:
* jdqwoi/TooManyMixed-LLM_04
* jdqwoi/TooManyMix_LLM_01
## Configuration
## Usage
| [
"# TooManyMix_LLM_02\n\nTooManyMix_LLM_02 is a merge of the following models using LazyMergekit:\n* jdqwoi/TooManyMixed-LLM_04\n* jdqwoi/TooManyMix_LLM_01",
"## Configuration",
"## Usage"
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_notata-seqsight_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_32768_512_43M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:38:19+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_32768\_512\_43M-L1\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation... | [
"### 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_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_32768_512_43M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_32768\_512\_43M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M 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_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_32768_512_43M-L8_f | null | [
"peft",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_32768\_512\_43M-L8\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M 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_300_notata-seqsight_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_32768_512_43M-L32_f | null | [
"peft",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_32768\_512\_43M-L32\_f
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_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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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_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_32768_512_43M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_32768\_512\_43M-L1\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation set:
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_all-seqsight_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_32768_512_43M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_32768\_512\_43M-L8\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M 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 |
# 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": []} | shallow6414/76m23o9 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cilantro9246/h222ims | 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 | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0430HMA9
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0430HMA9", "results": []}]} | Litzy619/O0430HMA9 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0430HMA9
=========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0218
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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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. -->
# trainer
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-... | {"license": "mit", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "microsoft/Phi-3-mini-4k-instruct", "model-index": [{"name": "trainer", "results": []}]} | Surabhi-K/phi3_15epochs | null | [
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#peft #safetensors #generated_from_trainer #base_model-microsoft/Phi-3-mini-4k-instruct #license-mit #region-us
|
# trainer
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct 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 hyperparamete... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0430HMA10
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0430HMA10", "results": []}]} | Litzy619/O0430HMA10 | null | [
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"generated_from_trainer",
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"license:apache-2.0",
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0430HMA10
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0559
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0430HMA11
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0430HMA11", "results": []}]} | Litzy619/O0430HMA11 | null | [
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0430HMA11
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0488
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0430HMA12
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0430HMA12", "results": []}]} | Litzy619/O0430HMA12 | null | [
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"generated_from_trainer",
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0430HMA12
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1479
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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text-generation | transformers | Quantizations of https://huggingface.co/Vezora/Narwhal-7b-v3
# From original readme
This is a merge model using Tie merge method.
Created using openchat 3.5 and una-cybertron-7b-v2-bf16.
Instruction template:
```python
import transformers
tokenizer = transformers.AutoTokenizer.from_pretrained("openchat/openchat_3.5"... | {"language": ["en"], "license": "other", "tags": ["transformers", "gguf", "imatrix", "Narwhal-7b-v3"], "pipeline_tag": "text-generation", "inference": false} | duyntnet/Narwhal-7b-v3-imatrix-GGUF | null | [
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#transformers #gguf #imatrix #Narwhal-7b-v3 #text-generation #en #license-other #region-us
| Quantizations of URL
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This is a merge model using Tie merge method.
Created using openchat 3.5 and una-cybertron-7b-v2-bf16.
Instruction template:
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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_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_32768_512_43M-L32_f | null | [
"peft",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_32768\_512\_43M-L32\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation set... | [
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null | null |
# kat33/Mixtral-8x7B-Instruct-v0.1-Q6_K-GGUF
This model was converted to GGUF format from [`mistralai/Mixtral-8x7B-Instruct-v0.1`](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [orig... | {"language": ["fr", "it", "de", "es", "en"], "license": "apache-2.0", "tags": ["llama-cpp", "gguf-my-repo"], "inference": {"parameters": {"temperature": 0.5}}, "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | kat33/Mixtral-8x7B-Instruct-v0.1-Q6_K-GGUF | null | [
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|
# kat33/Mixtral-8x7B-Instruct-v0.1-Q6_K-GGUF
This model was converted to GGUF format from 'mistralai/Mixtral-8x7B-Instruct-v0.1' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CL... | [
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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_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_32768_512_43M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_notata-seqsight\_32768\_512\_43M-L1\_f
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evaluat... | [
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text-generation | transformers |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_pat... | {"license": "other", "library_name": "transformers", "tags": ["autotrain", "text-generation-inference", "text-generation", "peft"], "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | nanxiz/autotrain-h731u-jdfg6 | null | [
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#transformers #tensorboard #safetensors #autotrain #text-generation-inference #text-generation #peft #conversational #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0430HMA14
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0430HMA14", "results": []}]} | Litzy619/O0430HMA14 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0430HMA14
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0186
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0430HMA15
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0430HMA15", "results": []}]} | Litzy619/O0430HMA15 | null | [
"safetensors",
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"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0430HMA15
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0266
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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text-to-image | diffusers |
# 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 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | Niggendar/mugenmalumixSDXL_v30 | null | [
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"region:us"
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"1910.09700"
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#diffusers #safetensors #arxiv-1910.09700 #endpoints_compatible #diffusers-StableDiffusionXLPipeline #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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null | null |
# NikolayKozloff/tweety-tatar-base-7b-2024-v1-Q8_0-GGUF
This model was converted to GGUF format from [`Tweeties/tweety-tatar-base-7b-2024-v1`](https://huggingface.co/Tweeties/tweety-tatar-base-7b-2024-v1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer... | {"language": ["tt"], "license": "apache-2.0", "tags": ["tweety", "llama-cpp", "gguf-my-repo"], "datasets": ["oscar-corpus/OSCAR-2301"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2"} | NikolayKozloff/tweety-tatar-base-7b-2024-v1-GGUF | null | [
"gguf",
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"llama-cpp",
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"dataset:oscar-corpus/OSCAR-2301",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-30T05:51:28+00:00 | [] | [
"tt"
] | TAGS
#gguf #tweety #llama-cpp #gguf-my-repo #tt #dataset-oscar-corpus/OSCAR-2301 #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
|
# NikolayKozloff/tweety-tatar-base-7b-2024-v1-Q8_0-GGUF
This model was converted to GGUF format from 'Tweeties/tweety-tatar-base-7b-2024-v1' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or ... | [
"# NikolayKozloff/tweety-tatar-base-7b-2024-v1-Q8_0-GGUF\nThis model was converted to GGUF format from 'Tweeties/tweety-tatar-base-7b-2024-v1' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke th... | [
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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_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_32768_512_43M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:56:16+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_notata-seqsight\_32768\_512\_43M-L8\_f
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evaluat... | [
"### 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_core_notata-seqsight_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_5... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_notata-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_32768_512_43M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:56:24+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_notata-seqsight\_32768\_512\_43M-L32\_f
==============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_notata dataset.
It achieves the following results on the evalu... | [
"### 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_core_tata-seqsight_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_32768_512_43M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:56:29+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_32768\_512\_43M-L1\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata 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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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_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_32768_512_43M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:57:21+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_32768\_512\_43M-L8\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata 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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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_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_32768_512_43M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:57:21+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_32768\_512\_43M-L32\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluation ... | [
"### 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. -->
# mistral-7b-dpo-full-sft-wo-kqa_golden
This model is a fine-tuned version of [Minbyul/mistral-7b-wo-kqa_golden-sft](https://huggi... | {"license": "apache-2.0", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "Minbyul/mistral-7b-wo-kqa_golden-sft", "model-index": [{"name": "mistral-7b-dpo-full-sft-wo-kqa_golden", "result... | Minbyul/mistral-7b-dpo-full-sft-wo-kqa_golden | null | [
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"text-generation",
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"base_model:Minbyul/mistral-7b-wo-kqa_golden-sft",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",... | null | 2024-04-30T05:57:27+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #alignment-handbook #trl #dpo #generated_from_trainer #dataset-HuggingFaceH4/ultrafeedback_binarized #base_model-Minbyul/mistral-7b-wo-kqa_golden-sft #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| mistral-7b-dpo-full-sft-wo-kqa\_golden
======================================
This model is a fine-tuned version of Minbyul/mistral-7b-wo-kqa\_golden-sft on the HuggingFaceH4/ultrafeedback\_binarized dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0018
* Rewards/chosen: -0.4458
* Rewards... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\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. -->
# mistral_envs_claim_finetune2
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/m... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral_envs_claim_finetune2", "results": []}]} | Haimee/mistral_envs_claim_finetune2 | null | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-30T05:58:26+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
|
# mistral_envs_claim_finetune2
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### T... | [
"# mistral_envs_claim_finetune2\n\nThis model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 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",
"##... | [
"TAGS\n#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us \n",
"# mistral_envs_claim_finetune2\n\nThis model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset.",
"## Model description\n\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_all-seqsight_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_32768_512_43M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_32768\_512\_43M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all 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_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_32768_512_43M-L8_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_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_32768\_512\_43M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all 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_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_4... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_32768_512_43M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T05:59:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_32768\_512\_43M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all 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 | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0430HMA16
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0430HMA16", "results": []}]} | Litzy619/O0430HMA16 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
] | null | 2024-04-30T06:03:10+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0430HMA16
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1386
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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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_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_32768_512_43M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T06:04:03+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_32768\_512\_43M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4907
* 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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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": []} | pruning/v16o0y7 | null | [
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#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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- License... | [
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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_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_32768_512_43M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T06:04:50+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_32768\_512\_43M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4984
* 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_EMP_H3K14ac-seqsight_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_32768_512_43M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T06:04:53+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_32768\_512\_43M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4924
* F1 Sco... | [
"### 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_EMP_H3K4me2-seqsight_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_43M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T06:05:02+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_43M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5889
* 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_EMP_H3K4me2-seqsight_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_43M-L8_f | null | [
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| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_43M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
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* Loss: 0.5958
* F1 Score... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "facebook/w2v-bert-2.0", "model-index": [{"name": "w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1", "results": []}]} | Sajjo/w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1 | null | [
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|
# w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: inf
- eval_wer: 0.4790
- eval_runtime: 231.2694
- eval_samples_per_second: 18.922
- eval_steps_per_second: 2.365
- ... | [
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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. -->
# token_classifier
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "token_classifier", "results": []}]} | madanagrawal/token_classifier | null | [
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| token\_classifier
=================
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2720
* Precision: 0.6096
* Recall: 0.3170
* F1: 0.4171
* Accuracy: 0.9426
Model description
-----------------
Mor... | [
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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": []} | ryanyeo/kirnect-2-koAlpaca-polyglot-5.8b-remote-5150step-8batch_5epoch | 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_H3K4me2-seqsight_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_43M-L32_f | null | [
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| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_43M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5885
* F1 Sco... | [
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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": []} | lunarsylph/mooncell_v36 | null | [
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|
# Model Card for Model ID
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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. -->
# main
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)... | {"license": "llama2", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "main", "results": []}]} | Huma97/llama2-EquityAdvisor | null | [
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| main
====
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4148
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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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": []} | ryanyeo/kirnect-2-koAlpaca-polyglot-5.8B-remote | null | [
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# Model Card for Model ID
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text-to-image | diffusers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | Niggendar/mightMixes15Ponyxl_pxlBurst | null | [
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null | null |
# DerekWolfie/llama-3-8B-Instruct-function-calling-v0.2-Q5_K_M-GGUF
This model was converted to GGUF format from [`mzbac/llama-3-8B-Instruct-function-calling-v0.2`](https://huggingface.co/mzbac/llama-3-8B-Instruct-function-calling-v0.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggm... | {"language": ["en"], "license": "llama3", "tags": ["llama-cpp", "gguf-my-repo"], "datasets": ["mzbac/function-calling-llama-3-format-v1.1"]} | DerekWolfie/dereks-llama-3-8B-Instruct-function-calling | null | [
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|
# DerekWolfie/llama-3-8B-Instruct-function-calling-v0.2-Q5_K_M-GGUF
This model was converted to GGUF format from 'mzbac/llama-3-8B-Instruct-function-calling-v0.2' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Inv... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_43M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_43M-L1\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4802
* F1 Score: 0... | [
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image-classification | transformers |
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metrics
loss: 0.3038078248500824
f1_macro: 0.7294036951655769
f1_micro: 0.899283031751451
f1_weighted: 0.8963777407391669
precision_macro: 0.8462013295295603
precision_micro: 0.899283031751451
precision_weighted: 0.9070935900298... | {"tags": ["autotrain", "image-classification"], "datasets": ["autotrain-swin-tiny-patch4-window7-224/autotrain-data"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/t... | Kushagra07/autotrain-swin-tiny-patch4-window7-224 | null | [
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|
# Model Trained Using AutoTrain
- Problem type: Image Classification
## Validation Metrics
loss: 0.3038078248500824
f1_macro: 0.7294036951655769
f1_micro: 0.899283031751451
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cilantro9246/ofeq1al | 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_EMP_H3K9ac-seqsight_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_43M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_43M-L8\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4635
* F1 Score: 0... | [
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | JD97/bart-typo | null | [
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"arxiv:1910.09700",
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"1910.09700"
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#transformers #safetensors #bart #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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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. -->
# 0.0001_withdpo_4iters_bs256_531lr_iter_2
This model is a fine-tuned version of [ZhangShenao/0.0_ablation_sample1_4iters_bs256_it... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ZhangShenao/0.0_ablation_sample1_4iters_bs256_iter_1", "model-index": [{"name": "0.0001_withdpo_4iters_bs256_531lr_iter_2", "results": []}]} | ShenaoZ/0.0001_withdpo_4iters_bs256_531lr_iter_2 | null | [
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# 0.0001_withdpo_4iters_bs256_531lr_iter_2
This model is a fine-tuned version of ZhangShenao/0.0_ablation_sample1_4iters_bs256_iter_1 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
Mo... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# robust_llm_pythia-31m_mz-133_WordLength_n-its-10-seed-4
This model is a fine-tuned version of [EleutherAI/pythia-31m](https://hu... | {"tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-31m", "model-index": [{"name": "robust_llm_pythia-31m_mz-133_WordLength_n-its-10-seed-4", "results": []}]} | AlignmentResearch/robust_llm_pythia-31m_mz-133_WordLength_n-its-10-seed-4 | null | [
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|
# robust_llm_pythia-31m_mz-133_WordLength_n-its-10-seed-4
This model is a fine-tuned version of EleutherAI/pythia-31m on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training ... | [
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unconditional-image-generation | diffusers |
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('fath2024/sd-class-butterfli... | {"license": "mit", "tags": ["pytorch", "diffusers", "unconditional-image-generation", "diffusion-models-class"]} | fath2024/sd-class-butterflies-64 | null | [
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#diffusers #safetensors #pytorch #unconditional-image-generation #diffusion-models-class #license-mit #diffusers-DDPMPipeline #region-us
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# Model Card for Unit 1 of the Diffusion Models Class
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text-generation | transformers | # Alsebay/Lorge-2x7B AWQ
- Model creator: [Alsebay](https://huggingface.co/Alsebay)
- Original model: [Lorge-2x7B](https://huggingface.co/Alsebay/Lorge-2x7B)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
### Example Python code
```python
from awq impo... | {"license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/Lorge-2x7B-AWQ | null | [
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| # Alsebay/Lorge-2x7B AWQ
- Model creator: Alsebay
- Original model: Lorge-2x7B
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, ... | [
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"# Alsebay/Lorge-2x7B AWQ\n\n- Model creator: Alsebay\n- Original model: Lorge-2x7B",
"## How to use",
"### Install the necessary... | [
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"TAGS\n#transformers #safetensors #mixtral #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #license-cc-by-nc-4.0 #text-generation-inference #region-us \n# Alsebay/Lorge-2x7B AWQ\n\n- Model creator: Alsebay\n- Original model: Lorge-2x7B## How to use### Install the necessary packages### Examp... |
null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | abhayesian/lat-poisoned-1-hh | null | [
"transformers",
"safetensors",
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"1910.09700"
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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"# Model Card for Model ID",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_32768_512_43M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_32768_512_43M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_43M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T06:20:57+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_43M-L32\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5028
* 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_EMP_H3K4me3-seqsight_32768_512_43M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_32768_512_43M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_32768_512_43M-L1_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T06:21:14+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_32768\_512\_43M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5776
* 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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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimi... |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-seqsight_32768_512_43M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_43M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_43M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_32768_512_43M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_32768_512_43M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_43M",
"region:us"
] | null | 2024-04-30T06:21:34+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_32768\_512\_43M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_43M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5802
* 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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"### 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* ... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_43M #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimi... |
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