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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/stablecell_v55 | null | [
"transformers",
"safetensors",
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"text-generation",
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"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T04:02:13+00:00 | [
"1910.09700"
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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]:
- 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_prom_prom_300_all-seqsight_32768_512_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:03:04+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_32768\_512\_30M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M 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_core_tata-seqsight_32768_512_30M-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_30M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:03:04+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_32768\_512\_30M-L32\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M 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. -->
# selfbiorag-7b-dpo-full-sft-wo-healthsearch_qa
This model is a fine-tuned version of [Minbyul/selfbiorag-7b-wo-healthsearch_qa-sf... | {"tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "Minbyul/selfbiorag-7b-wo-healthsearch_qa-sft", "model-index": [{"name": "selfbiorag-7b-dpo-full-sft-wo-healthsearch_qa", "results": []}]} | Minbyul/selfbiorag-7b-dpo-full-sft-wo-healthsearch_qa | null | [
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|
# selfbiorag-7b-dpo-full-sft-wo-healthsearch_qa
This model is a fine-tuned version of Minbyul/selfbiorag-7b-wo-healthsearch_qa-sft on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4465
- Rewards/chosen: -0.5929
- Rewards/rejected: -1.6772
- Rew... | [
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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_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_32768\_512\_30M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M 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 | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | HenryCai1129/adapter-llama-adaptertoxic2nontoxic-2k-search-50-0.0003 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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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.
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- 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_EMP_H3K14ac-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_EMP_H3K14ac-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:04:32+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_32768\_512\_30M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5313
* F1 Score... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_all-seqsight_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_3... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_32768_512_30M-L32_f | null | [
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"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_32768\_512\_30M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M 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_EMP_H3K14ac-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_EMP_H3K14ac-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:04:45+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_32768\_512\_30M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5169
* 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-classification | transformers | ## TextAttack Model Card
This `distilbert` model was fine-tuned using TextAttack. The model was fine-tuned
for 3 epochs with a batch size of 8,
a maximum sequence length of 512, and an initial learning rate of 3e-05.
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| ## TextAttack Model Card
This 'distilbert' model was fine-tuned using TextAttack. The model was fine-tuned
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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_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_EMP_H3K14ac-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_32768_512_30M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_32768\_512\_30M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5324
* F1 Sco... | [
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null | null |
# Model Card for Model ID
This code implements Support Vector Machines (SVMs) with two different kernels: linear and RBF. A model card should mention that the model is an SVM and potentially specify the available kernels.
## Model Details
The code demonstrates how the model is trained using the SVC class from scikit-... | {} | Ironclad313/SVM | null | [
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# Model Card for Model ID
This code implements Support Vector Machines (SVMs) with two different kernels: linear and RBF. A model card should mention that the model is an SVM and potentially specify the available kernels.
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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_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_EMP_H3K4me2-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_30M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_30M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6031
* F1 Score... | [
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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_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_EMP_H3K4me2-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_30M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_30M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5980
* F1 Score... | [
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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": []} | fruk19/hidaka_model | null | [
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#transformers #safetensors #vision-encoder-decoder #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
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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. -->
# aligner-v1-llama3-01
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-L... | {"license": "other", "library_name": "peft", "tags": ["trl", "orpo", "generated_from_trainer"], "base_model": "meta-llama/Meta-Llama-3-8B", "model-index": [{"name": "aligner-v1-llama3-01", "results": []}]} | Ksgk-fy/aligner-v1-llama3-01 | null | [
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| aligner-v1-llama3-01
====================
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset.
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* Loss: 1.4361
* Rewards/chosen: -0.0331
* Rewards/rejected: -0.0349
* Rewards/accuracies: 0.8333
* Rewards/margins: 0.0018
* Log... | [
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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_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_EMP_H3K4me2-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_30M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_30M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5996
* F1 Sco... | [
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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_30M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_30M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_30M-L1\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5056
* F1 Score: 0... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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# 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_30M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_30M-L8_f | null | [
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| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_30M-L8\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4849
* F1 Score: 0... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-vivos
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-xls-r-300m", "model-index": [{"name": "wav2vec2-base-vivos", "results": []}]} | Lasion/wav2vec2-xls-r-300m-vivos | null | [
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| wav2vec2-base-vivos
===================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5366
* Wer: 0.3320
Model description
-----------------
More information needed
Intended uses & limitations
------... | [
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null | transformers |
# Uploaded model
- **Developed by:** arvnoodle
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Phi-3-mini-4k-instruct
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/un... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/Phi-3-mini-4k-instruct"} | arvnoodle/hcl-phi3-it-3b-xml-json | null | [
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|
# Uploaded model
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- License: apache-2.0
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<img src="URL width="200"/>
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cilantro9246/7chhuyp | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# TooManyMix_LLM
TooManyMix_LLM is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [jdqwoi/TooManyMixed-LLM_01](https://huggingface.co/jdqwoi/TooManyMixed-LLM_01)
* [jdqwoi/TooManyMixed-LLM_02](https://huggingface.co/jdqwoi... | {"tags": ["merge", "mergekit", "lazymergekit", "jdqwoi/TooManyMixed-LLM_01", "jdqwoi/TooManyMixed-LLM_02"], "base_model": ["jdqwoi/TooManyMixed-LLM_01", "jdqwoi/TooManyMixed-LLM_02"]} | jdqwoi/TooManyMix_LLM | null | [
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|
# TooManyMix_LLM
TooManyMix_LLM is a merge of the following models using LazyMergekit:
* jdqwoi/TooManyMixed-LLM_01
* jdqwoi/TooManyMixed-LLM_02
## Configuration
## Usage
| [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | atsizelti/turkish_org_classifier_16k | null | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# GUE_EMP_H3K9ac-seqsight_32768_512_30M-L32_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_EMP_H3K9ac-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_30M-L32_f | null | [
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| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_30M-L32\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5096
* F1 Score:... | [
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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_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_EMP_H3K4me3-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:22:22+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_32768\_512\_30M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6279
* 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_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_EMP_H3K4me3-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:22:46+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_32768\_512\_30M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6199
* 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_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_EMP_H3K4me3-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:24:47+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_32768\_512\_30M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6248
* 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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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"]} | Rudolph314/poca-SoccerTwos | null | [
"ml-agents",
"tensorboard",
"onnx",
"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] | null | 2024-04-30T04:24:53+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",
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"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... |
text-generation | transformers |
# Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
Directly quantized 4bit model with `bitsandbytes`. Built with Meta Llama 3
We have a Google Colab Tesla T4 notebook for Llama-3 8b here: https://colab.research.google.com/drive/135ced7oHytdxu3N2DNe1Z0kqjyYIkDXp?usp=sharing
[<img src="htt... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "tags": ["unsloth", "transformers", "llama", "llama-3"]} | Akirami/vanilla-llama-3-8b-bnb-4bit | null | [
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"en",
"license:llama2",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-30T04:25:17+00:00 | [] | [
"en"
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#transformers #safetensors #llama #text-generation #unsloth #llama-3 #en #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
============================================================================
Directly quantized 4bit model with 'bitsandbytes'. Built with Meta Llama 3
We have a Google Colab Tesla T4 notebook for Llama-3 8b here: URL
<img src="URL width... | [] | [
"TAGS\n#transformers #safetensors #llama #text-generation #unsloth #llama-3 #en #license-llama2 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n"
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] |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisperFinetune
This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-tiny.en", "model-index": [{"name": "whisperFinetune", "results": []}]} | shljessie/whisperFinetune | null | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:openai/whisper-tiny.en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T04:25:36+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #base_model-openai/whisper-tiny.en #license-apache-2.0 #endpoints_compatible #region-us
| whisperFinetune
===============
This model is a fine-tuned version of openai/URL on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5745
* Wer: 28.7011
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
M... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
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"TAGS\n#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #base_model-openai/whisper-tiny.en #license-apache-2.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0... |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_32768_512_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_EMP_H4-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:26:10+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4-seqsight\_32768\_512\_30M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2787
* F1 Score: 0.8962
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text-classification | transformers |
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 1.065280795097351
f1_macro: 0.2095479509928179
f1_micro: 0.4584103512014787
f1_weighted: 0.2881768494245037
precision_macro: 0.1528034504004929
precision_micro: 0.4584103512014787
precision_weighted: 0.2101400500886... | {"tags": ["autotrain", "text-classification"], "datasets": ["autotrain-4vbeh-1p6bd/autotrain-data"], "widget": [{"text": "I love AutoTrain"}]} | AnirudhVV/autotrain-4vbeh-1p6bd | null | [
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"dataset:autotrain-4vbeh-1p6bd/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T04:29:37+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #xlm-roberta #text-classification #autotrain #dataset-autotrain-4vbeh-1p6bd/autotrain-data #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 1.065280795097351
f1_macro: 0.2095479509928179
f1_micro: 0.4584103512014787
f1_weighted: 0.2881768494245037
precision_macro: 0.1528034504004929
precision_micro: 0.4584103512014787
precision_weighted: 0.2101400500886... | [
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null | null | # Summer Keto ACV Gummies Avis France - Summer Keto Gummies Expériences, Prix
Summer Keto ACV Gummies Avis - Uni : L’ajustement et la perte de poids sont devenus populaires récemment. Les gens réfléchissent souvent beaucoup à leur apparence et à leur comportement. Les médias sociaux sont la principale raison pour laqu... | {} | VKapseln475/SummerKetoACV102 | null | [
"region:us"
] | null | 2024-04-30T04:31:06+00:00 | [] | [] | TAGS
#region-us
| # Summer Keto ACV Gummies Avis France - Summer Keto Gummies Expériences, Prix
Summer Keto ACV Gummies Avis - Uni : L’ajustement et la perte de poids sont devenus populaires récemment. Les gens réfléchissent souvent beaucoup à leur apparence et à leur comportement. Les médias sociaux sont la principale raison pour laqu... | [
"# Summer Keto ACV Gummies Avis France - Summer Keto Gummies Expériences, Prix\n\nSummer Keto ACV Gummies Avis - Uni : L’ajustement et la perte de poids sont devenus populaires récemment. Les gens réfléchissent souvent beaucoup à leur apparence et à leur comportement. Les médias sociaux sont la principale raison po... | [
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"# Summer Keto ACV Gummies Avis France - Summer Keto Gummies Expériences, Prix\n\nSummer Keto ACV Gummies Avis - Uni : L’ajustement et la perte de poids sont devenus populaires récemment. Les gens réfléchissent souvent beaucoup à leur apparence et à leur comportement. Les médias sociaux son... | [
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"TAGS\n#region-us \n# Summer Keto ACV Gummies Avis France - Summer Keto Gummies Expériences, Prix\n\nSummer Keto ACV Gummies Avis - Uni : L’ajustement et la perte de poids sont devenus populaires récemment. Les gens réfléchissent souvent beaucoup à leur apparence et à leur comportement. Les médias sociaux sont la p... |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_32768_512_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_EMP_H4-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:32:35+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4-seqsight\_32768\_512\_30M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2796
* F1 Score: 0.8974
* Accu... | [
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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": []} | terry69/tiny-llama-20p-full | null | [
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# WAV2VEC-FINETUNE-TAMIL-1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_11_0"], "base_model": "facebook/wav2vec2-xls-r-300m", "model-index": [{"name": "WAV2VEC-FINETUNE-TAMIL-1", "results": []}]} | Vignesh-M/WAV2VEC-FINETUNE-TAMIL-1 | null | [
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|
# WAV2VEC-FINETUNE-TAMIL-1
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_11_0 dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
##... | [
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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": []} | amks313/llama2_qa | null | [
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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.
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- 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_EMP_H4-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_EMP_H4-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_32768_512_30M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4-seqsight\_32768\_512\_30M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3352
* F1 Score: 0.8852
* Ac... | [
"### 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_H3-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_EMP_H3-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_32768_512_30M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3-seqsight\_32768\_512\_30M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3166
* F1 Score: 0.8704
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 1er_mod_eval
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown datas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-cased", "model-index": [{"name": "1er_mod_eval", "results": []}]} | edchaud/1er_mod_eval | null | [
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| 1er\_mod\_eval
==============
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6113
* Accuracy: 0.175
Model description
-----------------
More information needed
Intended uses & limitations
-------------------------... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | abc88767/model14 | 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 |
# Phi-3-128K-Instruct-ov-fp16-int4-asym
## Model Description
This is a version of the original [Phi-3-128K-Instruct](https://huggingface.co/microsoft/Phi-3-128k-instruct) model, converted to OpenVINO™ IR (Intermediate Representation) format for optimized inference on Intel® hardware. This model is created using the... | {"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["OpenVINO", "Phi-3", "PyTorch", "weight_compression", "optimum-intel"], "pipeline_tag": "text-generation"} | nsbendre25/Phi-3-mini-128k-instruct-ov-fp16-int4-asym | null | [
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|
# Phi-3-128K-Instruct-ov-fp16-int4-asym
## Model Description
This is a version of the original Phi-3-128K-Instruct model, converted to OpenVINO™ IR (Intermediate Representation) format for optimized inference on Intel® hardware. This model is created using the procedures detailed in the OpenVINO™ Notebooks reposito... | [
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null | span-marker | [Growth Matrix Reviews](https://jciodev.microsoftcrmportals.com/forums/general-discussion/56e0e0e2-f105-ef11-a81c-6045bd0b2619) It's vital to take note of that not all upgrade techniques are therapeutically or experimentally demonstrated, and numerous items advertised for these reasons might need guideline or logica... | {"language": ["en"], "license": "afl-3.0", "library_name": "span-marker", "tags": ["Growth Matrix Reviews"]} | growthmatrixreviews/growthmatrixreviews | 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_H3-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_EMP_H3-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_32768_512_30M-L8_f | null | [
"peft",
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"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3-seqsight\_32768\_512\_30M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3326
* F1 Score: 0.8657
* Accu... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3-seqsight_32768_512_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_EMP_H3-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:40:00+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3-seqsight\_32768\_512\_30M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3600
* F1 Score: 0.8564
* Ac... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4ac-seqsight_32768_512_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_EMP_H4ac-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:40:31+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4ac-seqsight\_32768\_512\_30M-L1\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5836
* F1 Score: 0.7005
... | [
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text-generation | transformers |
# TooManyMix_LLM_01
TooManyMix_LLM_01 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [jdqwoi/TooManyMixed-LLM_03](https://huggingface.co/jdqwoi/TooManyMixed-LLM_03)
* [jdqwoi/TooManyMix_LLM](https://huggingface.co/jdqwo... | {"tags": ["merge", "mergekit", "lazymergekit", "jdqwoi/TooManyMixed-LLM_03", "jdqwoi/TooManyMix_LLM"], "base_model": ["jdqwoi/TooManyMixed-LLM_03", "jdqwoi/TooManyMix_LLM"]} | jdqwoi/TooManyMix_LLM_01 | null | [
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"base_model:jdqwoi/TooManyMix_LLM",
"autotrain_compatible",
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"text-genera... | null | 2024-04-30T04:41:10+00:00 | [] | [] | TAGS
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|
# TooManyMix_LLM_01
TooManyMix_LLM_01 is a merge of the following models using LazyMergekit:
* jdqwoi/TooManyMixed-LLM_03
* jdqwoi/TooManyMix_LLM
## Configuration
## Usage
| [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | dahye1/generator_2 | 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. -->
# GUE_EMP_H4ac-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_EMP_H4ac-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:42:22+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4ac-seqsight\_32768\_512\_30M-L8\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5741
* F1 Score: 0.7114
... | [
"### 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_H4ac-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_EMP_H4ac-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:42:47+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4ac-seqsight\_32768\_512\_30M-L32\_f
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5936
* F1 Score: 0.715... | [
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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": []} | shallow6414/2vrd6jk | null | [
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|
# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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<!-- Provide a longer summary of what this model is. -->
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K79me3-seqsight_32768_512_30M-L1_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_EMP_H3K79me3-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_32768_512_30M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_32768\_512\_30M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4466
* F1 Sc... | [
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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/iaztpsp | null | [
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# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
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- Model type:
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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_H3K79me3-seqsight_32768_512_30M-L8_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_EMP_H3K79me3-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_32768_512_30M-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_30M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_32768\_512\_30M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4411
* F1 Sc... | [
"### 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. -->
# Codellama-finetuned-code
This model was trained from scratch on the None dataset.
## Model description
More informat... | {"library_name": "peft", "tags": ["generated_from_trainer"], "model-index": [{"name": "Codellama-finetuned-code", "results": []}]} | elinaparajuli/Codellama-finetuned-code | null | [
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#peft #tensorboard #safetensors #generated_from_trainer #region-us
|
# Codellama-finetuned-code
This model was trained from scratch on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparamet... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K79me3-seqsight_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_32768_512_30M-L32_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_30M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_32768\_512\_30M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4398
* F1 ... | [
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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": []} | hi000000/insta_merged_llama2_koen | null | [
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## 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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multiple-choice | 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. -->
# bert-base-uncased-finetuned-swag
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-unca... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["swag"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-uncased-finetuned-swag", "results": []}]} | souraviithmds/bert-base-uncased-finetuned-swag | null | [
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|
# bert-base-uncased-finetuned-swag
This model is a fine-tuned version of bert-base-uncased on the swag dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyper... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me1-seqsight_32768_512_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_EMP_H3K4me1-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_32768_512_30M-L1_f | null | [
"peft",
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"region:us"
] | null | 2024-04-30T04:56:06+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_32768\_512\_30M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5440
* 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_H3K4me1-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_EMP_H3K4me1-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:57:03+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_32768\_512\_30M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5415
* 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_H3K4me1-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_EMP_H3K4me1-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_32768_512_30M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:57:49+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_32768\_512\_30M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5543
* 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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text-classification | transformers |
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 1.0650867223739624
f1_macro: 0.2095479509928179
f1_micro: 0.4584103512014787
f1_weighted: 0.2881768494245037
precision_macro: 0.1528034504004929
precision_micro: 0.4584103512014787
precision_weighted: 0.210140050088... | {"tags": ["autotrain", "text-classification"], "datasets": ["autotrain-byt8e-zygc3/autotrain-data"], "widget": [{"text": "I love AutoTrain"}]} | Akhil-9640/autotrain-byt8e-zygc3 | null | [
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|
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 1.0650867223739624
f1_macro: 0.2095479509928179
f1_micro: 0.4584103512014787
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precision_micro: 0.4584103512014787
precision_weighted: 0.210140050088... | [
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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_finetune1
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_finetune1", "results": []}]} | Haimee/mistral_envs_claim_finetune1 | null | [
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"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-30T04:58:22+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_finetune1
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... | [
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text-generation | null |
# Smart-Lemon-Cookie-7B
These are GGUFs for the following model:
https://huggingface.co/FallenMerick/Smart-Lemon-Cookie-7B | {"tags": ["quantized", "4-bit", "6-bit", "8-bit", "GGUF", "merge", "mistral", "text-generation"], "model_name": "Smart-Lemon-Cookie-7B", "base_model": ["FallenMerick/Smart-Lemon-Cookie-7B"], "model_type": "mistral", "pipeline_tag": "text-generation"} | FallenMerick/Smart-Lemon-Cookie-7B-GGUF | null | [
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#gguf #quantized #4-bit #6-bit #8-bit #GGUF #merge #mistral #text-generation #base_model-FallenMerick/Smart-Lemon-Cookie-7B #region-us
|
# Smart-Lemon-Cookie-7B
These are GGUFs for the following model:
URL | [
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] |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K36me3-seqsight_32768_512_30M-L1_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_EMP_H3K36me3-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T04:59:56+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_32768\_512\_30M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5059
* F1 Sc... | [
"### 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_H3K36me3-seqsight_32768_512_30M-L8_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_EMP_H3K36me3-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:00:14+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_32768\_512\_30M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4964
* F1 Sc... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gemma-1.1-2b-it-genai-kb
This model is a fine-tuned version of [google/gemma-1.1-2b-it](https://huggingface.co/google/gemma-1.1-... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "google/gemma-1.1-2b-it", "model-index": [{"name": "gemma-1.1-2b-it-genai-kb", "results": []}]} | cohesionet/gemma-1.1-2b-it-genai-kb | null | [
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"trl",
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"generated_from_trainer",
"base_model:google/gemma-1.1-2b-it",
"license:gemma",
"region:us"
] | null | 2024-04-30T05:00:17+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-google/gemma-1.1-2b-it #license-gemma #region-us
| gemma-1.1-2b-it-genai-kb
========================
This model is a fine-tuned version of google/gemma-1.1-2b-it on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.2164
Model description
-----------------
More information needed
Intended uses & limitations
------------------... | [
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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. -->
# base-nsp-100000
This model is a fine-tuned version of [mhr2004/plm-nsp-100000](https://huggingface.co/mhr2004/plm-nsp-100000) on... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mhr2004/plm-nsp-100000", "model-index": [{"name": "base-nsp-100000", "results": []}]} | mhr2004/base-nsp-100000 | null | [
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"safetensors",
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"generated_from_trainer",
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"license:mit",
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"endpoints_compatible",
"region:us"
] | null | 2024-04-30T05:01:25+00:00 | [] | [] | TAGS
#transformers #safetensors #roberta #text-classification #generated_from_trainer #base_model-mhr2004/plm-nsp-100000 #license-mit #autotrain_compatible #endpoints_compatible #region-us
| base-nsp-100000
===============
This model is a fine-tuned version of mhr2004/plm-nsp-100000 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8933
* Accuracy: 0.4877
Model description
-----------------
More information needed
Intended uses & limitations
---------------... | [
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null | peft |
## Mongolian-Llama3
### Model Description
Mongolian-Llama3 implementation in Chat UI
[](https://colab.research.google.com/drive/1LC0xx4i9xqFmwn9l8T6vw25RIr-BP0Tq?usp=sharing])
Mongolian-Llama3 is the first open source... | {"language": ["mn", "en"], "license": "apache-2.0", "library_name": "peft", "tags": ["Mongolian", "QLora", "Llama3", "Instructed-model"]} | Dorjzodovsuren/Mongolian_Llama3 | null | [
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"Mongolian",
"QLora",
"Llama3",
"Instructed-model",
"mn",
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"license:apache-2.0",
"region:us"
] | null | 2024-04-30T05:01:28+00:00 | [] | [
"mn",
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] | TAGS
#peft #tensorboard #safetensors #Mongolian #QLora #Llama3 #Instructed-model #mn #en #license-apache-2.0 #region-us
|
## Mongolian-Llama3
! Alt Text
### Model Description
Mongolian-Llama3 implementation in Chat UI
![Open In Colab](URL
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question-answering | 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. -->
# shipping_qa_model_30_04_24
This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/ro... | {"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "base_model": "deepset/roberta-base-squad2", "model-index": [{"name": "shipping_qa_model_30_04_24", "results": []}]} | SurajSphinx/shipping_qa_model_30_04_24 | null | [
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"base_model:deepset/roberta-base-squad2",
"license:cc-by-4.0",
"endpoints_compatible",
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] | null | 2024-04-30T05:02:36+00:00 | [] | [] | TAGS
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| shipping\_qa\_model\_30\_04\_24
===============================
This model is a fine-tuned version of deepset/roberta-base-squad2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.8070
Model description
-----------------
More information needed
Intended uses & limitatio... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
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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 | null | [
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... | null | 2024-04-30T05:03:19+00:00 | [] | [] | TAGS
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# 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
| [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["unsloth"]} | trex5790/model_l3 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["unsloth"]} | choudhry2272/lora-adapter-legal-llm | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | null |
# kat33/Mixtral-8x7B-Instruct-v0.1-Q5_K_M-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 [or... | {"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-Q5_K_M-GGUF | null | [
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|
# kat33/Mixtral-8x7B-Instruct-v0.1-Q5_K_M-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.
... | [
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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": []} | nem012/gemma2b-5e-4 | null | [
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#transformers #safetensors #gemma #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- 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_EMP_H3K36me3-seqsight_32768_512_30M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_32768_512_30M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_32768\_512\_30M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4838
* F1 ... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_0-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_0-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_32768_512_30M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_0-seqsight\_32768\_512\_30M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5765
* F1 Score: 0.6868
* 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_0-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_0-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_32768_512_30M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:08:03+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_0-seqsight\_32768\_512\_30M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5609
* F1 Score: 0.7098
* 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-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. -->
# base-nsp-10000
This model is a fine-tuned version of [mhr2004/plm-nsp-10000](https://huggingface.co/mhr2004/plm-nsp-10000) on an... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mhr2004/plm-nsp-10000", "model-index": [{"name": "base-nsp-10000", "results": []}]} | mhr2004/base-nsp-10000 | null | [
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"license:mit",
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"region:us"
] | null | 2024-04-30T05:12:57+00:00 | [] | [] | TAGS
#transformers #safetensors #roberta #text-classification #generated_from_trainer #base_model-mhr2004/plm-nsp-10000 #license-mit #autotrain_compatible #endpoints_compatible #region-us
| base-nsp-10000
==============
This model is a fine-tuned version of mhr2004/plm-nsp-10000 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8886
* Accuracy: 0.4717
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_mouse_0-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_0-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_32768_512_30M-L32_f | null | [
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"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_0-seqsight\_32768\_512\_30M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6749
* F1 Score: 0.7122
*... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_1-seqsight_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_1-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_32768_512_30M-L1_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:13:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_1-seqsight\_32768\_512\_30M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2628
* F1 Score: 0.8828
* 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 | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
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- llm_int8_threshold: 6.0
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_1-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_1-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_32768_512_30M-L8_f | null | [
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| GUE\_mouse\_1-seqsight\_32768\_512\_30M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2485
* F1 Score: 0.8920
* A... | [
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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/tfj29zx | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_1-seqsight_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_1-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_32768_512_30M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_1-seqsight\_32768\_512\_30M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2432
* F1 Score: 0.8950
*... | [
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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_4-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_4-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:15:19+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_4-seqsight\_32768\_512\_30M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6056
* F1 Score: 0.6643
* 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 |
<!-- 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. -->
# biomistral-7b-dpo-full-sft-wo-kqa_golden
This model is a fine-tuned version of [Minbyul/biomistral-7b-wo-kqa_golden-sft](https:/... | {"license": "apache-2.0", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "Minbyul/biomistral-7b-wo-kqa_golden-sft", "model-index": [{"name": "biomistral-7b-dpo-full-sft-wo-kqa_golden", "... | Minbyul/biomistral-7b-dpo-full-sft-wo-kqa_golden | null | [
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... | null | 2024-04-30T05:15:21+00:00 | [] | [] | TAGS
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=========================================
This model is a fine-tuned version of Minbyul/biomistral-7b-wo-kqa\_golden-sft on the HuggingFaceH4/ultrafeedback\_binarized dataset.
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* Loss: 0.4647
* Rewards/chosen: -0.3056
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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": []} | cilantro9246/7g1iirk | null | [
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"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
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"region:us"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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text-generation | null |
# TC-instruct-DPO - Typhoon 7B - GGUF
## Description
This repo contains GGUF format model files for [tanamettpk's TC Instruct DPO](https://huggingface.co/tanamettpk/TC-instruct-DPO).
## Quick jump
<span style="font-size:1.125em;">[**Jump to Downloads**](#provided-files).</span>
### About GGUF
GGUF is a new format... | {"language": ["en", "th"], "license": "apache-2.0", "tags": ["Mistral", "instruct", "finetune", "chatml", "DPO", "RLHF", "synthetic data"], "datasets": ["Thaweewat/alpaca-cleaned-52k-th", "yahma/alpaca-cleaned", "pythainlp/thaisum", "thai_toxicity_tweet", "pythainlp/thainer-corpus-v2", "Thaweewat/instruct-qa-thai-combi... | pek111/TC-instruct-DPO-GGUF | null | [
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===================================
Description
-----------
This repo contains GGUF format model files for tanamettpk's TC Instruct DPO.
Quick jump
----------
Jump to Downloads.
### About GGUF
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null | transformers |
# Uploaded model
- **Developed by:** arvnoodle
- **License:** apache-2.0
- **Finetuned from model :** Phind/Phind-CodeLlama-34B-v2
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslot... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "Phind/Phind-CodeLlama-34B-v2"} | arvnoodle/hcl-phind-codellama34b-xml-json | null | [
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|
# Uploaded model
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- License: apache-2.0
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<img src="URL width="200"/>
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_4-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_4-seqsight_32768_512_30M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_32768_512_30M-L8_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
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] | null | 2024-04-30T05:17:47+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_4-seqsight\_32768\_512\_30M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6048
* F1 Score: 0.6543
* 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_4-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_4-seqsight_32768_512_30M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_32768_512_30M-L32_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_4-seqsight\_32768\_512\_30M-L32\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6249
* F1 Score: 0.6690
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-large-plm-nsp-1000
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unk... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "roberta-large", "model-index": [{"name": "roberta-large-plm-nsp-1000", "results": []}]} | mhr2004/roberta-large-plm-nsp-1000 | null | [
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] | null | 2024-04-30T05:18:43+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-1000
==========================
This model is a fine-tuned version of roberta-large on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6936
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: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20",
"### Train... | [
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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-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_3-seqsight_32768_512_30M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_32768_512_30M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-30T05:19:24+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_mouse\_3-seqsight\_32768\_512\_30M-L1\_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: 0.5528
* F1 Score: 0.7865
* 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 | transformers |
# Uploaded model
- **Developed by:** universalml
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslo... | {"language": ["en", "ne"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | universalml/NepaliGPT | null | [
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|
# Uploaded model
- Developed by: universalml
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/> | [
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] | [
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