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text-generation | transformers |
# andreass123/gemma-2b-translation-v0.150-Q4_K_M-GGUF
This model was converted to GGUF format from [`lemon-mint/gemma-2b-translation-v0.150`](https://huggingface.co/lemon-mint/gemma-2b-translation-v0.150) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer... | {"language": ["ko"], "license": "gemma", "library_name": "transformers", "tags": ["gemma", "pytorch", "instruct", "finetune", "translation", "llama-cpp", "gguf-my-repo"], "base_model": "lemon-mint/gemma-ko-1.1-2b-it", "widget": [{"messages": [{"role": "user", "content": "Translate into Korean:Hamsters don't eat cats."}... | andreass123/gemma-2b-translation-v0.150-Q4_K_M-GGUF | null | [
"transformers",
"gguf",
"gemma",
"pytorch",
"instruct",
"finetune",
"translation",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"ko",
"base_model:lemon-mint/gemma-ko-1.1-2b-it",
"license:gemma",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T01:14:11+00:00 | [] | [
"ko"
] | TAGS
#transformers #gguf #gemma #pytorch #instruct #finetune #translation #llama-cpp #gguf-my-repo #text-generation #ko #base_model-lemon-mint/gemma-ko-1.1-2b-it #license-gemma #endpoints_compatible #region-us
|
# andreass123/gemma-2b-translation-v0.150-Q4_K_M-GGUF
This model was converted to GGUF format from 'lemon-mint/gemma-2b-translation-v0.150' 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 t... | [
"# andreass123/gemma-2b-translation-v0.150-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'lemon-mint/gemma-2b-translation-v0.150' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the... | [
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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_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](http... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_16384_512_56M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T01:15:25+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_16384\_512\_56M-L8\_f
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4826
* F1 Score: 0... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_16384_512_56M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T01:16:19+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_16384\_512\_56M-L32\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5010
* 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_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_16384_512_56M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T01:17:22+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_16384\_512\_56M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5803
* 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 | transformers | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/databricks/dbrx-instruct
(actually the f16 from https://huggingface.co/dranger003/dbrx-instruct-iMat.GGUF as llama.cpp seems to have broken ... | {"language": ["en"], "library_name": "transformers", "base_model": "databricks/dbrx-instruct", "quantized_by": "mradermacher"} | mradermacher/dbrx-instruct-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:databricks/dbrx-instruct",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T01:19:02+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-databricks/dbrx-instruct #endpoints_compatible #region-us
| About
-----
static quants of URL
(actually the f16 from URL as URL seems to have broken dbrx support currently)
weighted/imatrix quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part file... | [] | [
"TAGS\n#transformers #gguf #en #base_model-databricks/dbrx-instruct #endpoints_compatible #region-us \n"
] | [
33
] | [
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] |
null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA20
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA20", "results": []}]} | Litzy619/O0428HMA20 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
] | null | 2024-04-30T01:19:14+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA20
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1352
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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null | transformers |
# Uploaded model
- **Developed by:** Kairaz
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/ma... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | Kairaz/games | null | [
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|
# Uploaded model
- Developed by: Kairaz
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# trainer
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-... | {"license": "mit", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "microsoft/Phi-3-mini-4k-instruct", "model-index": [{"name": "trainer", "results": []}]} | Surabhi-K/trainer | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:microsoft/Phi-3-mini-4k-instruct",
"license:mit",
"region:us"
] | null | 2024-04-30T01:20:54+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-microsoft/Phi-3-mini-4k-instruct #license-mit #region-us
|
# trainer
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparamete... | [
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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-finetune
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) o... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-uncased-finetune", "results": []}]} | avikumar/bert-base-uncased-finetune | null | [
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"tensorboard",
"safetensors",
"bert",
"multiple-choice",
"generated_from_trainer",
"base_model:bert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T01:21:16+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #multiple-choice #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #endpoints_compatible #region-us
| bert-base-uncased-finetune
==========================
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7793
* Accuracy: 0.7993
Model description
-----------------
More information needed
Intended uses & limitation... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA9
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA9", "results": []}]} | Litzy619/O0428HMA9 | null | [
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
] | null | 2024-04-30T01:21:17+00:00 | [] | [] | TAGS
#generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA9
=========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0545
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed... | [
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null | peft |
# 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. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "microsoft/Phi-3-mini-4k-instruct"} | Surabhi-K/phi3_18epochs | null | [
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#peft #safetensors #arxiv-1910.09700 #base_model-microsoft/Phi-3-mini-4k-instruct #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
#... | [
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text-generation | transformers | <a href="https://www.gradient.ai" target="_blank"><img src="https://cdn-uploads.huggingface.co/production/uploads/655bb613e8a8971e89944f3e/TSa3V8YpoVagnTYgxiLaO.png" width="200"/></a>
# Llama-3 8B Gradient Instruct 1048k
Gradient incorporates your data to deploy autonomous assistants that power critical operations acr... | {"language": ["en"], "license": "llama3", "tags": ["meta", "llama-3"], "pipeline_tag": "text-generation"} | blockblockblock/Llama-3-8B-Instruct-Gradient-1048k-bpw3.5-exl2 | null | [
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#transformers #safetensors #llama #text-generation #meta #llama-3 #conversational #en #license-llama3 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| [<img src="URL width="200"/>](URL)
Llama-3 8B Gradient Instruct 1048k
==================================
Gradient incorporates your data to deploy autonomous assistants that power critical operations across your business. If you're looking to build custom AI models or agents, email us a message contact@URL.
For m... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
"#### Transformers pipeline",
"#### Transformers AutoModelForCausalLM",
"### Use with 'llama3'\n\n\n... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-rating-poem
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingfac... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["poem_sentiment"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-rating-poem", "results": [{"task": {"type": "text-classification", "name": "Text Classificatio... | VuaCoBac/distilbert-base-uncased-finetuned-rating-poem | null | [
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| distilbert-base-uncased-finetuned-rating-poem
=============================================
This model is a fine-tuned version of distilbert-base-uncased on the poem\_sentiment dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1902
* Accuracy: 0.8762
* F1: 0.8765
Model description
------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
"### Training... | [
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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": []} | jski/UltraMerge-v2-7B | 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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- Shared by [optional]:
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["unsloth", "trl", "sft"]} | clarkchan/llama3-8b-alpaca-cn | 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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"TAGS\n#transformers #safetensors #llama #text-generation #unsloth #trl #sft #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-seqsight_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_16384_512_56M-L8_f | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_16384\_512\_56M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5969
* 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_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_16384_512_56M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
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"region:us"
] | null | 2024-04-30T01:27:48+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_16384\_512\_56M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7298
* F1 Sco... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H4-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_16384_512_56M-L1_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T01:27:53+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H4-seqsight\_16384\_512\_56M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2576
* F1 Score: 0.9083
* 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-generation | transformers |
## Exllama v2 Quantizations of starcoder2-15b-instruct-v0.1
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.20">turboderp's ExLlamaV2 v0.0.20</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each b... | {"license": "bigcode-openrail-m", "library_name": "transformers", "tags": ["code"], "datasets": ["bigcode/self-oss-instruct-sc2-exec-filter-50k"], "pipeline_tag": "text-generation", "base_model": "bigcode/starcoder2-15b", "quantized_by": "bartowski", "model-index": [{"name": "starcoder2-15b-instruct-v0.1", "results": [... | bartowski/starcoder2-15b-instruct-v0.1-exl2 | null | [
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"model-index",
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] | null | 2024-04-30T01:28:20+00:00 | [] | [] | TAGS
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| Exllama v2 Quantizations of starcoder2-15b-instruct-v0.1
--------------------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.20 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
Each branch contains an individual bits... | [] | [
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] |
null | null | quantized_by: KnightCodin
---
## Exllama v2 Quantizations of <a href="https://huggingface.co/winglian/llama-3-8b-256k-PoSE"> winglian/llama-3-8b-256k-PoSE </a>
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.19">turboderp's ExLlamaV2 v0.0.19</a> for quantization.
<b>The "main" branch only con... | {"language": ["en"], "license": "cc-by-nc-4.0"} | Knightcodin/Llama-3-8b-256k-PoSE-exl2 | null | [
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#en #arxiv-2309.10400 #license-cc-by-nc-4.0 #region-us
| quantized\_by: KnightCodin
--------------------------
Exllama v2 Quantizations of <a href="URL winglian/llama-3-8b-256k-PoSE
----------------------------------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.19 for quantization.
**The "main" branch only contains the URL, download one of the ... | [
"### Use with transformers\n\n\nSee the snippet below for usage with Transformers:",
"### Use with 'llama3'\n\n\nPlease, follow the instructions in the repository.\n\n\nTo download Original checkpoints, see the example command below leveraging 'huggingface-cli':\n\n\nFor Hugging Face support, we recommend using t... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H4-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_16384_512_56M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H4-seqsight\_16384\_512\_56M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2737
* F1 Score: 0.9018
* 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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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_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H4-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_16384_512_56M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H4-seqsight\_16384\_512\_56M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2550
* F1 Score: 0.9006
* Ac... | [
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null | null | # 🌋 LLaVA: Large Language and Vision Assistant
*Visual instruction tuning towards large language and vision models with GPT-4 level capabilities.*
[[Project Page](https://llava-vl.github.io/)] [[Paper](https://arxiv.org/abs/2304.08485)] [[Demo](https://llava.hliu.cc/)] [[Data](https://huggingface.co/datasets/liuhao... | {} | multitensor/mistal-llava | null | [
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#safetensors #arxiv-2304.08485 #arxiv-2306.14895 #arxiv-2306.00890 #arxiv-2305.07895 #endpoints_compatible #region-us
| LLaVA: Large Language and Vision Assistant
==========================================
*Visual instruction tuning towards large language and vision models with GPT-4 level capabilities.*
[Project Page] [Paper] [Demo] [Data] [Model]
Visual Instruction Tuning
Haotian Liu\*, Chunyuan Li\*, Qingyang Wu, Yong Jae L... | [
"### Upgrade to latest code base\n\n\nLLaVA Weights\n-------------\n\n\nWe release LLaVA weights as delta weights to comply with the LLaMA model license.\nYou can add our delta to the original LLaMA weights to obtain the LLaVA weights.\n\n\nInstructions:\n\n\n1. Get the original LLaMA weights in the huggingface for... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | lunarsylph/mooncell_v34 | 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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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. -->
# bert-finetuned-squad
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unkno... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-cased", "model-index": [{"name": "bert-finetuned-squad", "results": []}]} | AlexYang33/bert-finetuned-sql | null | [
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|
# bert-finetuned-squad
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
... | [
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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"... | [
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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. -->
# output_dir
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) o... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/deberta-v3-base", "model-index": [{"name": "output_dir", "results": []}]} | tralon/test-v4 | null | [
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# output_dir
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset.
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- Accuracy: 0.9667
## Model description
More information needed
## Intended uses & limitations
More information needed
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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/nr5v2la | 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 |
# Introducing Mermaid-Llama-6.7B-RAG
Powered by 6.7 billion parameters, this model sets the bar for excellence in
AI-driven code comprehension and narrative visualization now with further reduction of hallucinations inspired by https://huggingface.co/jondurbin
who created the "Context-Obedient" chat template. We sta... | {"license": "cc-by-4.0"} | TroyDoesAI/Mermaid-Llama-6.7B-RAG | null | [
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|
# Introducing Mermaid-Llama-6.7B-RAG
Powered by 6.7 billion parameters, this model sets the bar for excellence in
AI-driven code comprehension and narrative visualization now with further reduction of hallucinations inspired by URL
who created the "Context-Obedient" chat template. We stand on the shoulders of Giants... | [
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text-generation | transformers | <a href="https://www.gradient.ai" target="_blank"><img src="https://cdn-uploads.huggingface.co/production/uploads/655bb613e8a8971e89944f3e/TSa3V8YpoVagnTYgxiLaO.png" width="200"/></a>
# Llama-3 8B Gradient Instruct 1048k
Gradient incorporates your data to deploy autonomous assistants that power critical operations acr... | {"language": ["en"], "license": "llama3", "tags": ["meta", "llama-3"], "pipeline_tag": "text-generation"} | blockblockblock/Llama-3-8B-Instruct-Gradient-1048k-bpw3.7-exl2 | null | [
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| [<img src="URL width="200"/>](URL)
Llama-3 8B Gradient Instruct 1048k
==================================
Gradient incorporates your data to deploy autonomous assistants that power critical operations across your business. If you're looking to build custom AI models or agents, email us a message contact@URL.
For m... | [
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"#### Transformers pipeline",
"#### Transformers AutoModelForCausalLM",
"### Use with 'llama3'\n\n\n... | [
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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/gi2xkq1 | 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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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | williamchenaeo/ppo-LunarLander-v2 | null | [
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#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA10
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA10", "results": []}]} | Litzy619/O0428HMA10 | null | [
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| O0428HMA10
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1456
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - yuffish/kettle-segmented
This is a dreambooth model derived from stabilityai/stable-diffusion-2-1-base. Th... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "inference": true, "base_model": "stabilityai/stable-diffusion-2-1-base", "instance_prompt": "a photo of sks object"} | yuffish/kettle-segmented | null | [
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|
# DreamBooth - yuffish/kettle-segmented
This is a dreambooth model derived from stabilityai/stable-diffusion-2-1-base. The weights were trained on a photo of sks object using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
## Intended uses & ... | [
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text-generation | transformers |
pretrained speculative draft model. based on llama3 tokenizer. trained < 4B tokens. | {"language": ["en"], "license": "apache-2.0"} | maywell/l3-211m | null | [
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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. -->
# NTTU-digital-TA-gemma
This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) on a... | {"license": "gemma", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "google/gemma-2b-it", "model-index": [{"name": "NTTU-digital-TA-gemma", "results": []}]} | NTTUNLPTEAM/NTTU-digital-TA-gemma | null | [
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|
# NTTU-digital-TA-gemma
This model is a fine-tuned version of google/gemma-2b-it on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparamete... | [
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text-generation | transformers | # Untitled Model (1)
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method.
### Models Merged
The following models were included in the mer... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["codellama/CodeLlama-7b-hf", "EleutherAI/llemma_7b"]} | JyoP/merged_llemma_codeLlama | null | [
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| # Untitled Model (1)
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the linear merge method.
### Models Merged
The following models were included in the merge:
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null | peft |
# 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. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "t5-base"} | PQlet/T5base-lora-sumarizationTables-v2-MLM-lambda0.1 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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- Funded by [optional]:
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- Finetuned from model [optional]:
### Model Sources [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_EMP_H3-seqsight_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_16384_512_56M-L1_f | null | [
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| GUE\_EMP\_H3-seqsight\_16384\_512\_56M-L1\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2977
* F1 Score: 0.8871
* 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_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_16384_512_56M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3-seqsight\_16384\_512\_56M-L8\_f
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3045
* F1 Score: 0.8824
* 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_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_16384_512_56M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T01:53:32+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3-seqsight\_16384\_512\_56M-L32\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2646
* F1 Score: 0.8951
* 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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text-generation | transformers | <a href="https://www.gradient.ai" target="_blank"><img src="https://cdn-uploads.huggingface.co/production/uploads/655bb613e8a8971e89944f3e/TSa3V8YpoVagnTYgxiLaO.png" width="200"/></a>
# Llama-3 8B Gradient Instruct 1048k
Gradient incorporates your data to deploy autonomous assistants that power critical operations acr... | {"language": ["en"], "license": "llama3", "tags": ["meta", "llama-3"], "pipeline_tag": "text-generation"} | blockblockblock/Llama-3-8B-Instruct-Gradient-1048k-bpw4-exl2 | null | [
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#transformers #safetensors #llama #text-generation #meta #llama-3 #conversational #en #license-llama3 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| [<img src="URL width="200"/>](URL)
Llama-3 8B Gradient Instruct 1048k
==================================
Gradient incorporates your data to deploy autonomous assistants that power critical operations across your business. If you're looking to build custom AI models or agents, email us a message contact@URL.
For m... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
"#### Transformers pipeline",
"#### Transformers AutoModelForCausalLM",
"### Use with 'llama3'\n\n\n... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4ac-seqsight_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_16384_512_56M-L1_f | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H4ac-seqsight\_16384\_512\_56M-L1\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5400
* F1 Score: 0.7389
... | [
"### 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 |
# 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. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "Mistral-7B-Instruct-v0.2"} | NandGate1110/mistral-7b-bakery | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
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- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
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#... | [
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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_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_16384_512_56M-L8_f | null | [
"peft",
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"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T02:00:22+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H4ac-seqsight\_16384\_512\_56M-L8\_f
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5424
* F1 Score: 0.7384
... | [
"### 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-healthsearch_qa
This model is a fine-tuned version of [Minbyul/biomistral-7b-wo-healthsearch_qa-sf... | {"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-healthsearch_qa-sft", "model-index": [{"name": "biomistral-7b-dpo-full-sft-wo-healthsea... | Minbyul/biomistral-7b-dpo-full-sft-wo-healthsearch_qa | null | [
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"autotrain_compatible... | null | 2024-04-30T02:01:03+00:00 | [] | [] | TAGS
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# biomistral-7b-dpo-full-sft-wo-healthsearch_qa
This model is a fine-tuned version of Minbyul/biomistral-7b-wo-healthsearch_qa-sft on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6929
- Rewards/chosen: 0.0003
- Rewards/rejected: -0.0003
- Rewa... | [
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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": []} | tduch/gemma-7b-it-adapters-alex-street | null | [
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4ac-seqsight_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_16384_512_56M-L32_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T02:02:06+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H4ac-seqsight\_16384\_512\_56M-L32\_f
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5443
* F1 Score: 0.741... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA11
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA11", "results": []}]} | Litzy619/O0428HMA11 | null | [
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| O0428HMA11
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0353
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | cilantro9246/w2vxdwf | 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]:
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null | peft |
# 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. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "mistralai/Mistral-7B-Instruct-v0.2"} | Charishma27/sft_mistral_709_steps_3_apple_sampled_epoch | null | [
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# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
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- License:
- Finetuned from model [optional]:
### Model Sources [optional]
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null | transformers |
# Uploaded model
- **Developed by:** dmorrigan
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | dmorrigan/HebrewLyricsLoRA-40K-5Epoch | null | [
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# Uploaded model
- Developed by: dmorrigan
- 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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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/nlfv3uy | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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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. -->
# financial-sentiment-model-1000-samples
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "financial-sentiment-model-1000-samples", "results": []}]} | kevinwlip/financial-sentiment-model-1000-samples | null | [
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|
# financial-sentiment-model-1000-samples
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7525
- Accuracy: 0.7
- F1: 0.7
## Model description
More information needed
## Intended uses & limitations
More informa... | [
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summarization | transformers |
# indobart-small
This model is a fine-tuned version of [bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on [Liputan6](https://paperswithcode.com/dataset/liputan6) dataset.
See demo model here [notebook](https://colab.research.google.com/drive/1bcqS42M3e5IySPYtAa-S4UeyJczg9DXh?usp=sharing).
## Training... | {"language": ["id"], "license": "mit", "tags": ["bart"], "datasets": ["id_liputan6"], "metrics": ["rouge"], "pipeline_tag": "summarization"} | gaduhhartawan/indobart-base | null | [
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| indobart-small
==============
This model is a fine-tuned version of bart-large-cnn on Liputan6 dataset.
See demo model here notebook.
Training procedure
------------------
### Training hyperparameters
* learning\_rate: 0.0001
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas... | [
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text-generation | transformers | <a href="https://www.gradient.ai" target="_blank"><img src="https://cdn-uploads.huggingface.co/production/uploads/655bb613e8a8971e89944f3e/TSa3V8YpoVagnTYgxiLaO.png" width="200"/></a>
# Llama-3 8B Gradient Instruct 1048k
Gradient incorporates your data to deploy autonomous assistants that power critical operations acr... | {"language": ["en"], "license": "llama3", "tags": ["meta", "llama-3"], "pipeline_tag": "text-generation"} | blockblockblock/Llama-3-8B-Instruct-Gradient-1048k-bpw4.2-exl2 | null | [
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| [<img src="URL width="200"/>](URL)
Llama-3 8B Gradient Instruct 1048k
==================================
Gradient incorporates your data to deploy autonomous assistants that power critical operations across your business. If you're looking to build custom AI models or agents, email us a message contact@URL.
For m... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
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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_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_56M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_56M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4296
* 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. -->
# GUE_EMP_H3K79me3-seqsight_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_56M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_56M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4254
* 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. -->
# GUE_EMP_H3K79me3-seqsight_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_16384_512_56M-L32_f | null | [
"peft",
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-30T02:12:33+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_16384\_512\_56M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4267
* F1 ... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me1-seqsight_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_56M-L1_f | null | [
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| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_56M-L1\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
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* Loss: 0.5118
* F1 Score... | [
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text-generation | transformers |
# 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:** Andrew Chahnwoo Park
- **Model type:** LLaMA
- **Language(s) (NLP):** English
- **License:** apac... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "datasets": ["databricks/databricks-dolly-15k"]} | Chahnwoo/TinyLlama-1.1B-Chat-v1.0-0.05E-QLoRA-Databricks-SFT-Test_20240430 | null | [
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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. -->
# model_name-finetuned-squad
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmind... | {"tags": ["generated_from_trainer"], "base_model": "aubmindlab/bert-base-arabertv2", "model-index": [{"name": "model_name-finetuned-squad", "results": []}]} | omarezz/model_name-finetuned-squad | null | [
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| model\_name-finetuned-squad
===========================
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.9280
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_EMP_H3K4me1-seqsight_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_56M-L8_f | null | [
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| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_56M-L8\_f
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5147
* F1 Score... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - yuffish/colon-04
This is a dreambooth model derived from stabilityai/stable-diffusion-2-1-base. The weight... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "inference": true, "base_model": "stabilityai/stable-diffusion-2-1-base", "instance_prompt": "a photo of sks object"} | yuffish/colon-04 | null | [
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... | null | 2024-04-30T02:16:26+00:00 | [] | [] | TAGS
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|
# DreamBooth - yuffish/colon-04
This is a dreambooth model derived from stabilityai/stable-diffusion-2-1-base. The weights were trained on a photo of sks object using DreamBooth.
You can find some example images in the following.
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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. -->
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | zinoli/image_text | null | [
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null | transformers |
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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null | null |
<!-- WEASEL: AUTO-GENERATED DOCS START (do not remove) -->
# 🪐 Weasel Project: Citations of ECFR Banking Regulation in a spaCy pipeline.
Custom text classification project for spaCy v3 adapted from the spaCy v3
## 📋 project.yml
The [`project.yml`](project.yml) defines the data assets required by the
project, as ... | {"language": "en", "tags": ["machine learning", "natural language processing", "huggingface"]} | DagimB/ecfr-textcat | null | [
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| Weasel Project: Citations of ECFR Banking Regulation in a spaCy pipeline.
=========================================================================
Custom text classification project for spaCy v3 adapted from the spaCy v3
URL
---
The 'URL' defines the data assets required by the
project, as well as the available ... | [
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text-generation | transformers | <a href="https://www.gradient.ai" target="_blank"><img src="https://cdn-uploads.huggingface.co/production/uploads/655bb613e8a8971e89944f3e/TSa3V8YpoVagnTYgxiLaO.png" width="200"/></a>
# Llama-3 8B Gradient Instruct 1048k
Gradient incorporates your data to deploy autonomous assistants that power critical operations acr... | {"language": ["en"], "license": "llama3", "tags": ["meta", "llama-3"], "pipeline_tag": "text-generation"} | blockblockblock/Llama-3-8B-Instruct-Gradient-1048k-bpw4.4-exl2 | null | [
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| [<img src="URL width="200"/>](URL)
Llama-3 8B Gradient Instruct 1048k
==================================
Gradient incorporates your data to deploy autonomous assistants that power critical operations across your business. If you're looking to build custom AI models or agents, email us a message contact@URL.
For m... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
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"#### Transformers AutoModelForCausalLM",
"### Use with 'llama3'\n\n\n... | [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mistral-7b-dpo-full-sft-wo-healthsearch_qa
This model is a fine-tuned version of [Minbyul/mistral-7b-wo-healthsearch_qa-sft](htt... | {"license": "apache-2.0", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrafeedback_binarized"], "base_model": "Minbyul/mistral-7b-wo-healthsearch_qa-sft", "model-index": [{"name": "mistral-7b-dpo-full-sft-wo-healthsearch_qa... | Minbyul/mistral-7b-dpo-full-sft-wo-healthsearch_qa | null | [
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|
# mistral-7b-dpo-full-sft-wo-healthsearch_qa
This model is a fine-tuned version of Minbyul/mistral-7b-wo-healthsearch_qa-sft on the HuggingFaceH4/ultrafeedback_binarized dataset.
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- Loss: 0.6746
- Rewards/chosen: -0.0204
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA12
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA12", "results": []}]} | Litzy619/O0428HMA12 | null | [
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| O0428HMA12
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1467
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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text-generation | transformers |
# Model Card for Model ID
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## Model Details
### Model Description
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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": []} | lleticiasilvaa/1B-datasetMenor-10epochs | 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 | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA22
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA22", "results": []}]} | Litzy619/O0428HMA22 | null | [
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA22
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0467
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA21
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA21", "results": []}]} | Litzy619/O0428HMA21 | null | [
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| O0428HMA21
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0514
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA24
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA24", "results": []}]} | Litzy619/O0428HMA24 | null | [
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA24
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0551
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ft-facebook-bart-large-xsum-on-samsum
This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/fa... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "facebook/bart-large-xsum", "model-index": [{"name": "ft-facebook-bart-large-xsum-on-samsum", "results": []}]} | mrami010/ft-facebook-bart-large-xsum-on-samsum | null | [
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#transformers #safetensors #bart #text2text-generation #generated_from_trainer #base_model-facebook/bart-large-xsum #license-mit #autotrain_compatible #endpoints_compatible #region-us
| ft-facebook-bart-large-xsum-on-samsum
=====================================
This model is a fine-tuned version of facebook/bart-large-xsum on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.5249
* Rouge1: 50.3616
* Rouge2: 25.1246
* Rougel: 41.214
* Rougelsum: 46.1946
* Gen Len:... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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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_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_16384_512_56M-L32_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_16384\_512\_56M-L32\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5103
* 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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sentence-similarity | peft |
# LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
> LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fin... | {"language": ["en"], "license": "mit", "library_name": "peft", "tags": ["text-embedding", "embeddings", "information-retrieval", "beir", "text-classification", "language-model", "text-clustering", "text-semantic-similarity", "text-evaluation", "text-reranking", "feature-extraction", "sentence-similarity", "Sentence Sim... | McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised | null | [
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"natu... | null | 2024-04-30T02:35:26+00:00 | [
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# LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
> LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fin... | [
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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_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_56M-L1_f | null | [
"peft",
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_56M-L1\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4564
* 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_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](ht... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_56M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_56M-L8\_f
==================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4559
* 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 | null | This is a copy of zero123-xl model from https://zero123.cs.columbia.edu/, please refer [their spaces: https://huggingface.co/cvlab](https://huggingface.co/cvlab) for more information.
| {} | kealiu/zero123-xl | null | [
"region:us"
] | null | 2024-04-30T02:37:23+00:00 | [] | [] | TAGS
#region-us
| This is a copy of zero123-xl model from URL please refer their spaces: URL for more information.
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA26
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA26", "results": []}]} | Litzy619/O0428HMA26 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA26
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1367
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# O0428HMA25
This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "allenai/OLMo-1B", "model-index": [{"name": "O0428HMA25", "results": []}]} | Litzy619/O0428HMA25 | null | [
"safetensors",
"generated_from_trainer",
"base_model:allenai/OLMo-1B",
"license:apache-2.0",
"region:us"
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#safetensors #generated_from_trainer #base_model-allenai/OLMo-1B #license-apache-2.0 #region-us
| O0428HMA25
==========
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0179
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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text-generation | transformers | <a href="https://www.gradient.ai" target="_blank"><img src="https://cdn-uploads.huggingface.co/production/uploads/655bb613e8a8971e89944f3e/TSa3V8YpoVagnTYgxiLaO.png" width="200"/></a>
# Llama-3 8B Gradient Instruct 1048k
Gradient incorporates your data to deploy autonomous assistants that power critical operations acr... | {"language": ["en"], "license": "llama3", "tags": ["meta", "llama-3"], "pipeline_tag": "text-generation"} | blockblockblock/Llama-3-8B-Instruct-Gradient-1048k-bpw4.6-exl2 | null | [
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"text-generation-inference",
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#transformers #safetensors #llama #text-generation #meta #llama-3 #conversational #en #license-llama3 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| [<img src="URL width="200"/>](URL)
Llama-3 8B Gradient Instruct 1048k
==================================
Gradient incorporates your data to deploy autonomous assistants that power critical operations across your business. If you're looking to build custom AI models or agents, email us a message contact@URL.
For m... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
"#### Transformers pipeline",
"#### Transformers AutoModelForCausalLM",
"### Use with 'llama3'\n\n\n... | [
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text2text-generation | transformers | test | {} | shrms/chart_korea | null | [
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"autotrain_compatible",
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#transformers #pytorch #pix2struct #text2text-generation #autotrain_compatible #endpoints_compatible #region-us
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null | peft |
Used MonsterAPI for Finetuning
# Model Card for eswardivi/llamathon_v1
Model is Finetuned on microsoft/orca-math-word-problems-200k using MonsterAPI No finetuning
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a long... | {"license": "apache-2.0", "library_name": "peft", "datasets": ["microsoft/orca-math-word-problems-200k"], "base_model": "meta-llama/Meta-Llama-3-8B-Instruct"} | eswardivi/llamathon_v1 | null | [
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"license:apache-2.0",
"region:us"
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#peft #safetensors #dataset-microsoft/orca-math-word-problems-200k #base_model-meta-llama/Meta-Llama-3-8B-Instruct #license-apache-2.0 #region-us
|
Used MonsterAPI for Finetuning
# Model Card for eswardivi/llamathon_v1
Model is Finetuned on microsoft/orca-math-word-problems-200k using MonsterAPI No finetuning
# Model Card for Model ID
## Model Details
### Model Description
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null | transformers |
# Uploaded model
- **Developed by:** MilaNguyen
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsl... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | MilaNguyen/sft_summary_1 | null | [
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# Uploaded model
- Developed by: MilaNguyen
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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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_16384_512_56M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_EMP_H3K36me3-seqsight_16384_512_56M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_56M-L32_f | null | [
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| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_56M-L32\_f
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_EMP\_H3K36me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5081
* 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": []} | armaniii/llama-3-8b-argument-detection | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# 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": []} | kyounghyun/eeve-levware-k-240430 | 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 | 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_16384_512_56M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_56M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_56M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_mouse\_0-seqsight\_16384\_512\_56M-L1\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5589
* F1 Score: 0.7250
* A... | [
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sentence-similarity | peft |
> LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine-tuned to achieve state-of-the-art performance.
- **Repository:** ht... | {"language": ["en"], "license": "mit", "library_name": "peft", "tags": ["text-embedding", "embeddings", "information-retrieval", "beir", "text-classification", "language-model", "text-clustering", "text-semantic-similarity", "text-evaluation", "text-reranking", "feature-extraction", "sentence-similarity", "Sentence Sim... | McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-unsup-simcse | null | [
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- Repository: URL
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text-generation | transformers |
# Model Details
Saltlux, AI Labs 언어모델팀에서 학습 및 공개한 <b>Ko-Llama3-Luxia-8B</b> 모델은 Meta에서 출시한 Llama-3-8B 모델을 <b>한국어에 특화</b>한 모델입니다.<br><br>
자체 보유하고 있는 1TB 이상의 한국어 학습 데이터 중, 약 100GB 정도의 데이터를 선별하여 사전학습에 활용하였습니다.<br><br>
또한 공개된 Llama-3 Tokenizer를 한국어로 확장하고 사전학습에 활용했습니다.
- **Meta Llama-3:** Meta developed and released the M... | {"language": ["en", "ko"], "license": "llama3", "tags": ["saltlux", "luxia", "meta", "llama-3", "pytorch"], "pipeline_tag": "text-generation"} | saltlux/Ko-Llama3-Luxia-8B | null | [
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| Model Details
=============
Saltlux, AI Labs 언어모델팀에서 학습 및 공개한 **Ko-Llama3-Luxia-8B** 모델은 Meta에서 출시한 Llama-3-8B 모델을 **한국어에 특화**한 모델입니다.
자체 보유하고 있는 1TB 이상의 한국어 학습 데이터 중, 약 100GB 정도의 데이터를 선별하여 사전학습에 활용하였습니다.
또한 공개된 Llama-3 Tokenizer를 한국어로 확장하고 사전학습에 활용했습니다.
* Meta Llama-3: Meta developed and released the M... | [
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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_16384_512_56M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_mouse_0-seqsight_16384_512_56M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_56M-L8_f | null | [
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| GUE\_mouse\_0-seqsight\_16384\_512\_56M-L8\_f
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_mouse\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8034
* F1 Score: 0.7222
* A... | [
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null | transformers |
# Model Card for Model ID
Gemma 2B function calling. [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) finetuned on [hypervariance/function-calling-sharegpt](https://huggingface.co/datasets/hypervariance/function-calling-sharegpt).
## Usage
Make sure you have the [peft](https://huggingface.co/docs/pef... | {"library_name": "transformers", "datasets": ["hypervariance/function-calling-sharegpt"]} | bodhicitta/gemma-2b-function-call | null | [
"transformers",
"safetensors",
"dataset:hypervariance/function-calling-sharegpt",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T02:48:41+00:00 | [] | [] | TAGS
#transformers #safetensors #dataset-hypervariance/function-calling-sharegpt #endpoints_compatible #region-us
|
# Model Card for Model ID
Gemma 2B function calling. google/gemma-2b-it finetuned on hypervariance/function-calling-sharegpt.
## Usage
Make sure you have the peft package installed. You can install it with 'pip install peft'.
You can also use sharegpt formatted prompts:
## Prompt template
Function calls a... | [
"# Model Card for Model ID\n\nGemma 2B function calling. google/gemma-2b-it finetuned on hypervariance/function-calling-sharegpt.",
"## Usage\n\nMake sure you have the peft package installed. You can install it with 'pip install peft'.\n\n\n\n\nYou can also use sharegpt formatted prompts:",
"## Prompt template\... | [
"TAGS\n#transformers #safetensors #dataset-hypervariance/function-calling-sharegpt #endpoints_compatible #region-us \n",
"# Model Card for Model ID\n\nGemma 2B function calling. google/gemma-2b-it finetuned on hypervariance/function-calling-sharegpt.",
"## Usage\n\nMake sure you have the peft package installed.... | [
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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": []} | uh1216/society-textbook-Llama3-8b-Instruct-10epoch | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T02:48:48+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
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"# Model Card for Model ID",
"## Model Details",
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"TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n# Model Card for Model ID## Model Details### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funde... |
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": []} | MohammadKarami/hard-roberta | null | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-30T02:49:10+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #roberta #text-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s)... | [
"TAGS\n#transformers #safetensors #roberta #text-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This mod... | [
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