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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": []} | bdsaglam/llama-2-7b-chat-jerx-peft-2i4dmlfd | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Uploaded model
- **Developed by:** codesagar
- **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/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | codesagar/prompt-guard-classification-v8 | null | [
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# Uploaded model
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null | transformers |
# Uploaded model
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- **License:** apache-2.0
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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/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | codesagar/prompt-guard-reasoning-v8 | null | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# phi-1_5-2024-04-16-18-39-xe7pE
This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_... | {"license": "mit", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "microsoft/phi-1_5", "model-index": [{"name": "phi-1_5-2024-04-16-18-39-xe7pE", "results": []}]} | frenkd/phi-1_5-2024-04-16-18-39-xe7pE | null | [
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# phi-1_5-2024-04-16-18-39-xe7pE
This model is a fine-tuned version of microsoft/phi-1_5 on the generator dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hy... | [
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null | mlx |
# mlx-community/CodeQwen1.5-7B-Chat-4bit
This model was converted to MLX format from [`Qwen/CodeQwen1.5-7B-Chat`]() using mlx-lm version **0.9.0**.
Model added by [Prince Canuma](https://twitter.com/Prince_Canuma).
Refer to the [original model card](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat) for more details o... | {"license": "apache-2.0", "tags": ["mlx"]} | mlx-community/CodeQwen1.5-7B-Chat-4bit | null | [
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# mlx-community/CodeQwen1.5-7B-Chat-4bit
This model was converted to MLX format from ['Qwen/CodeQwen1.5-7B-Chat']() using mlx-lm version 0.9.0.
Model added by Prince Canuma.
Refer to the original model card for more details on the model.
## Use with mlx
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multiple-choice | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# sahithya20/bert-base-cased-mcq-swag
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "bert-base-cased", "model-index": [{"name": "sahithya20/bert-base-cased-mcq-swag", "results": []}]} | sahithya20/bert-base-cased-mcq-swag | null | [
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| sahithya20/bert-base-cased-mcq-swag
===================================
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.4182
* Train Accuracy: 0.8560
* Validation Loss: 0.9197
* Validation Accuracy: 0.6680
* Epoch:... | [
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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. -->
# mt5-base-finetuned-en-to-tr-colab
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "google/mt5-base", "model-index": [{"name": "mt5-base-finetuned-en-to-tr-colab", "results": []}]} | Justice0893/mt5-base-finetuned-en-to-tr-colab | null | [
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| mt5-base-finetuned-en-to-tr-colab
=================================
This model is a fine-tuned version of google/mt5-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: nan
* Bleu: 0.0851
* Gen Len: 7.1921
Model description
-----------------
More information needed
Int... | [
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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. -->
# autoregressive_finetune_split_rate2e-05_epochs4
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingfac... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert/distilgpt2", "model-index": [{"name": "autoregressive_finetune_split_rate2e-05_epochs4", "results": []}]} | katieguo/autoregressive_finetune_split_rate2e-05_epochs4 | null | [
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| autoregressive\_finetune\_split\_rate2e-05\_epochs4
===================================================
This model is a fine-tuned version of distilbert/distilgpt2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 3.4420
Model description
-----------------
More information ne... | [
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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": []} | Revrse/blip-icon-captioning | null | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K36me3-seqsight_16384_512_56M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_512_56M]... | {"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_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K36me3-seqsight_16384_512_56M-L32_all | null | [
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"safetensors",
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| GUE\_EMP\_H3K36me3-seqsight\_16384\_512\_56M-L32\_all
=====================================================
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: 0.9688
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 1536\n* eval\\_batch\\_size: 1536\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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audio-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-finetuned-ks
This model is a fine-tuned version of [motheecreator/wav2vec2-base-finetuned-ks](https://huggingface.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["accuracy"], "base_model": "motheecreator/wav2vec2-base-finetuned-ks", "model-index": [{"name": "wav2vec2-base-finetuned-ks", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dat... | motheecreator/wav2vec2-base-finetuned-ks | null | [
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| wav2vec2-base-finetuned-ks
==========================
This model is a fine-tuned version of motheecreator/wav2vec2-base-finetuned-ks on the audiofolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0117
* Accuracy: 0.9982
Model description
-----------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\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. -->
# idefics2-8b-docvqa-finetuned-tutorial
This model is a fine-tuned version of [HuggingFaceM4/idefics2-8b](https://huggingface.co/H... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "HuggingFaceM4/idefics2-8b", "model-index": [{"name": "idefics2-8b-docvqa-finetuned-tutorial", "results": []}]} | raejeong/idefics2-8b-docvqa-finetuned-tutorial | null | [
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"license:apache-2.0",
"region:us"
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#safetensors #generated_from_trainer #base_model-HuggingFaceM4/idefics2-8b #license-apache-2.0 #region-us
|
# idefics2-8b-docvqa-finetuned-tutorial
This model is a fine-tuned version of HuggingFaceM4/idefics2-8b on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
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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. -->
# autoregressive_finetune_split_rate2e-05_epochs3
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingfac... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert/distilgpt2", "model-index": [{"name": "autoregressive_finetune_split_rate2e-05_epochs3", "results": []}]} | katieguo/autoregressive_finetune_split_rate2e-05_epochs3 | null | [
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| autoregressive\_finetune\_split\_rate2e-05\_epochs3
===================================================
This model is a fine-tuned version of distilbert/distilgpt2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 3.5220
Model description
-----------------
More information ne... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | zandfj/Llama-2-7b-chat-hf-qlora-nq-ret-robust | null | [
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] | [] | 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... | [
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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. -->
# V0415B2
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
I... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "V0415B2", "results": []}]} | Litzy619/V0415B2 | null | [
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"generated_from_trainer",
"base_model:microsoft/phi-2",
"license:mit",
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| V0415B2
=======
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0627
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
T... | [
"### 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 | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/mergekit-community/mergekit-dare_ties-ymiqjtz
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. I... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "mergekit-community/mergekit-dare_ties-ymiqjtz", "quantized_by": "mradermacher"} | mradermacher/mergekit-dare_ties-ymiqjtz-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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null | 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": []} | vishesh-t27/fine_tune_phi | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"1910.09700"
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Orin27/beans_classifier
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-ba... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "Orin27/beans_classifier", "results": []}]} | Orin27/beans_classifier | null | [
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| Orin27/beans\_classifier
========================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.2283
* Validation Loss: 0.1632
* Train Accuracy: 0.9710
* Epoch: 2
Model description
-----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'module': 'keras.optimizers.schedules', 'class\\_name': 'PolynomialDecay', 'config': {'initial\\_learning\\_rate': 3e-05, 'decay\\_steps': 2481, 'end\\_learni... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/microsoft/WizardLM-2-8x22B
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/WizardLM-2-8x2... | {"language": ["en"], "library_name": "transformers", "base_model": "microsoft/WizardLM-2-8x22B", "quantized_by": "mradermacher"} | mradermacher/WizardLM-2-8x22B-i1-GGUF | null | [
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"en",
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"en"
] | TAGS
#transformers #gguf #en #base_model-microsoft/WizardLM-2-8x22B #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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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": [], "widget": [{"example_title": "\u0935\u0930\u094d\u0924\u092e\u093e\u0928 \u092a\u094d\u0930\u0927\u093e\u0928\u092e\u0902\u0924\u094d\u0930\u0940", "messages": [{"role": "user", "content": "\u092d\u093e\u0930\u0924 \u0915\u0947 \u0935\u0930\u094d\u0924\u092e\u093e\u0928 \u09... | makers-lab/Indus-1.1B-IT | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
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null | transformers |
Layout model for [surya](https://github.com/VikParuchuri/surya). | {"license": "cc-by-nc-sa-4.0"} | vikp/surya_layout2 | null | [
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Layout model for surya. | [] | [
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text-generation | transformers | # karakuri-midrose-mg
モデルの詳細は、[こちら](https://huggingface.co/sbtom/karakuri-midroze-mg.gguf)です。 | {"language": ["ja"], "tags": ["merge"], "pipeline_tag": "text-generation"} | sbtom/karakuri-midroze-mg | null | [
"transformers",
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#transformers #safetensors #llama #text-generation #merge #ja #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
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モデルの詳細は、こちらです。 | [
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null | transformers |
Reading order model for [surya](https://github.com/VikParuchuri/surya). | {"license": "cc-by-nc-sa-4.0"} | vikp/surya_order | null | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us"
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#transformers #safetensors #vision-encoder-decoder #license-cc-by-nc-sa-4.0 #endpoints_compatible #region-us
|
Reading order model for surya. | [] | [
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text-generation | transformers | # karakuri-midroze-CV
モデルの詳細は、[こちら](https://huggingface.co/sbtom/karakuri-midrose-CV.gguf)です。
| {"language": ["ja"], "tags": ["merge"], "pipeline_tag": "text-generation"} | sbtom/karakuri-midrose-CV | null | [
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#transformers #safetensors #llama #text-generation #merge #ja #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # karakuri-midroze-CV
モデルの詳細は、こちらです。
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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. -->
# OpenAI GPT-2 355M
## Model description
This custom GPT-2 model is derived from the [gpt2-medium](https://huggingface.co/gpt2-me... | {"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tatsu-lab/alpaca"], "widget": [{"text": "\nYou are a chat bot that provides professional answers to questions asked\n\n### Instruction:\nWhat is the purpose of life\n\n### Response:"}], "pipeline_tag": "text-generation", "model-ind... | anezatra/gpt2-alpaca-355M | null | [
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"en",
"dataset:tatsu-lab/alpaca",
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"text-generation-inference",
"region:us"
] | null | 2024-04-16T17:05:59+00:00 | [] | [
"en"
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|
# OpenAI GPT-2 355M
## Model description
This custom GPT-2 model is derived from the gpt2-medium model and trained on the Alpaca dataset. Anezatra team meticulously trained this model on the Alpaca dataset for natural language processing tasks. The model excels in text generation and language understanding tasks, ... | [
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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. -->
# model_hh_shp4_dpo1
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_shp4_dpo1", "results": []}]} | guoyu-zhang/model_hh_shp4_dpo1 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-16T17:09:42+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_shp4\_dpo1
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4317
* Rewards/chosen: -6.5985
* Rewards/rejected: -6.9380
* Rewards/accuracies: 0.5200
* Rewards/margins: 0.3394
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\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=... | [
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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. -->
# model_hh_usp2_dpo5
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_usp2_dpo5", "results": []}]} | guoyu-zhang/model_hh_usp2_dpo5 | null | [
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] | null | 2024-04-16T17:12:50+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_usp2\_dpo5
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3713
* Rewards/chosen: -6.8988
* Rewards/rejected: -10.4722
* Rewards/accuracies: 0.5700
* Rewards/margins: 3.5734... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\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=... | [
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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-L32_all
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_mouse_0-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_0-seqsight_16384_512_56M-L32_all | 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-L32\_all
================================================
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: 2.2545
* F1 Score: 0.60... | [
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-am
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unkn... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-finetuned-am", "results": []}]} | HankLiuML/bert-finetuned-am | null | [
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"license:apache-2.0",
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"region:us"
] | null | 2024-04-16T17:14:52+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #token-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-finetuned-am
=================
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: 0.4629
* Precision: 0.3961
* Recall: 0.6021
* F1: 0.4779
* Accuracy: 0.8443
Model description
-----------------
More information nee... | [
"### 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: 10",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_1-seqsight_16384_512_56M-L32_all
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_mouse_1-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_1-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T17:15:06+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_mouse\_1-seqsight\_16384\_512\_56M-L32\_all
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_mouse\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4853
* F1 Score: 0.80... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | OwOOwO/dumbo-krillin30 | null | [
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"text-generation",
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Shared by [optional]:
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- License... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_4-seqsight_16384_512_56M-L32_all
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_mouse_4-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_4-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T17:15:48+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_mouse\_4-seqsight\_16384\_512\_56M-L32\_all
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_mouse\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8050
* F1 Score: 0.58... | [
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text-generation | transformers |
# Spaetzle-v63-7b
Spaetzle-v63-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [OpenPipe/mistral-ft-optimized-1227](https://huggingface.co/OpenPipe/mistral-ft-optimized-1227)
* [DiscoResearch/DiscoLM_German_7b_v1](htt... | {"tags": ["merge", "mergekit", "lazymergekit", "OpenPipe/mistral-ft-optimized-1227", "DiscoResearch/DiscoLM_German_7b_v1"], "base_model": ["OpenPipe/mistral-ft-optimized-1227", "DiscoResearch/DiscoLM_German_7b_v1"]} | cstr/Spaetzle-v63-7b | null | [
"transformers",
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"merge",
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"lazymergekit",
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"base_model:OpenPipe/mistral-ft-optimized-1227",
"base_model:DiscoResearch/DiscoLM_German_7b_v1",
"autotrain_compatible"... | null | 2024-04-16T17:16:54+00:00 | [] | [] | TAGS
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# Spaetzle-v63-7b
Spaetzle-v63-7b is a merge of the following models using LazyMergekit:
* OpenPipe/mistral-ft-optimized-1227
* DiscoResearch/DiscoLM_German_7b_v1
## Configuration
## Usage
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_3-seqsight_16384_512_56M-L32_all
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_mouse_3-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_3-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T17:18:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_mouse\_3-seqsight\_16384\_512\_56M-L32\_all
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_mouse\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 3.3338
* F1 Score: 0.68... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\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 | sentence-transformers |
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | seniichev/me5-wb | null | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"feature-extraction",
"sentence-similarity",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T17:20:07+00:00 | [] | [] | TAGS
#sentence-transformers #safetensors #xlm-roberta #feature-extraction #sentence-similarity #endpoints_compatible #region-us
|
# {MODEL_NAME}
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
Then you can u... | [
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co/apple/mobilevit-xx-small) on an ... | {"license": "other", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "apple/mobilevit-xx-small", "model-index": [{"name": "results", "results": []}]} | JoshuaKelleyDs/doodle-MobileVIT-xxs-finetune | null | [
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"generated_from_trainer",
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"license:other",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T17:26:03+00:00 | [] | [] | TAGS
#transformers #onnx #safetensors #mobilevit #image-classification #generated_from_trainer #base_model-apple/mobilevit-xx-small #license-other #autotrain_compatible #endpoints_compatible #region-us
| results
=======
This model is a fine-tuned version of apple/mobilevit-xx-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1665
* Accuracy: 0.7093
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/KaeriJenti/kaori-72b-v1
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/kaori-72b-v1-GGUF... | {"language": ["en"], "license": "unknown", "library_name": "transformers", "base_model": "KaeriJenti/kaori-72b-v1", "quantized_by": "mradermacher"} | mradermacher/kaori-72b-v1-i1-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:KaeriJenti/kaori-72b-v1",
"license:unknown",
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"en"
] | TAGS
#transformers #gguf #en #base_model-KaeriJenti/kaori-72b-v1 #license-unknown #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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text-generation | null |
## Llamacpp Quantizations of WizardLM-2-8x22B
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2675">b2675</a> for quantization.
Original model: https://huggingface.co/microsoft/WizardLM-2-8x22B
## Prompt format
```
{system_... | {"license": "apache-2.0", "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/WizardLM-2-8x22B-GGUF | null | [
"gguf",
"text-generation",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T17:30:47+00:00 | [] | [] | TAGS
#gguf #text-generation #license-apache-2.0 #region-us
| Llamacpp Quantizations of WizardLM-2-8x22B
------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
Prompt format
-------------
Download a file (not the whole branch) from below:
--------------------------------------------------
Which file shou... | [] | [
"TAGS\n#gguf #text-generation #license-apache-2.0 #region-us \n"
] | [
21
] | [
"TAGS\n#gguf #text-generation #license-apache-2.0 #region-us \n"
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video-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. -->
# videomae-base-finetuned-isl-numbers
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU... | {"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "MCG-NJU/videomae-base", "model-index": [{"name": "videomae-base-finetuned-isl-numbers", "results": []}]} | latif98/videomae-base-finetuned-isl-numbers | null | [
"transformers",
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"videomae",
"video-classification",
"generated_from_trainer",
"base_model:MCG-NJU/videomae-base",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T17:31:29+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #videomae #video-classification #generated_from_trainer #base_model-MCG-NJU/videomae-base #license-cc-by-nc-4.0 #endpoints_compatible #region-us
| videomae-base-finetuned-isl-numbers
===================================
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1287
* Accuracy: 0.6444
Model description
-----------------
More information needed
Inte... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio: ... | [
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null | null |
# NSK-128k-7B-slerp-GGUF ⭐️⭐️⭐️⭐️
NSK-7B-128k-slerp is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [Nitral-AI/Nyan-Stunna-7B](https://huggingface.co/Nitral-AI/Nyan-Stunna-7B)
* [Nitral-AI/Kunocchini-7b-128k-test](https://huggingface.co/Nitral-AI/Kunocchini-7b-128k-test)
## ... | {"language": ["en", "ru", "th"], "license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "Nitral-AI/Nyan-Stunna-7B", "Nitral-AI/Kunocchini-7b-128k-test", "gguf", "Q2_K", "Q3_K_L", "Q3_K_M", "Q3_K_S", "Q4_0", "Q4_1", "Q4_K_S", "Q4_k_m", "Q5_0", "Q5_1", "Q6_K", "Q5_K_S", "Q5_k_m", "Q8_0", "128k"]} | AlekseiPravdin/NSK-128k-7B-slerp-gguf | null | [
"gguf",
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#gguf #merge #mergekit #lazymergekit #Nitral-AI/Nyan-Stunna-7B #Nitral-AI/Kunocchini-7b-128k-test #Q2_K #Q3_K_L #Q3_K_M #Q3_K_S #Q4_0 #Q4_1 #Q4_K_S #Q4_k_m #Q5_0 #Q5_1 #Q6_K #Q5_K_S #Q5_k_m #Q8_0 #128k #en #ru #th #license-apache-2.0 #region-us
|
# NSK-128k-7B-slerp-GGUF ⭐️⭐️⭐️⭐️
NSK-7B-128k-slerp is a merge of the following models using mergekit:
* Nitral-AI/Nyan-Stunna-7B
* Nitral-AI/Kunocchini-7b-128k-test
## Configuration
Eval embedding benchmark (with 70 specific quesions):
!URL
!URL
!URL
!URL
!URL
!URL
!URL
!URL
!URL
!URL
!URL
!URL
!URL
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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": []} | pandafm/donutES-UMU | null | [
"transformers",
"safetensors",
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"endpoints_compatible",
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] | null | 2024-04-16T17:34:15+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #vision-encoder-decoder #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/mergekit-community/mergekit-slerp-exkkzvd
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If th... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "mergekit-community/mergekit-slerp-exkkzvd", "quantized_by": "mradermacher"} | mradermacher/mergekit-slerp-exkkzvd-GGUF | null | [
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"endpoints_compatible",
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"en"
] | TAGS
#transformers #gguf #mergekit #merge #en #base_model-mergekit-community/mergekit-slerp-exkkzvd #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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null | peft | Finetuned Mistral-7b model for medical document summarization
### Framework versions
- PEFT 0.10.1.dev0 | {"license": "mit", "library_name": "peft", "base_model": "mistralai/Mistral-7B-v0.1"} | BiswajitPadhi99/mistral-7b-finetuned-medical-summarizer | null | [
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"base_model:mistralai/Mistral-7B-v0.1",
"license:mit",
"region:us"
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#peft #safetensors #base_model-mistralai/Mistral-7B-v0.1 #license-mit #region-us
| Finetuned Mistral-7b model for medical document summarization
### Framework versions
- PEFT 0.10.1.dev0 | [
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null | peft |
# Model Card
gemma-2b fine-tuned on gsm8k "question" field. LoRA rank 8.
### Framework versions
- PEFT 0.10.0
| {"library_name": "peft", "base_model": "google/gemma-2b"} | jacobthebanana/example-gemma-2b-lora-gsm8k | null | [
"peft",
"safetensors",
"base_model:google/gemma-2b",
"region:us"
] | null | 2024-04-16T17:43:47+00:00 | [] | [] | TAGS
#peft #safetensors #base_model-google/gemma-2b #region-us
|
# Model Card
gemma-2b fine-tuned on gsm8k "question" field. LoRA rank 8.
### Framework versions
- PEFT 0.10.0
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] |
text-generation | transformers | # pythontestmerge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
Catastrophic forgetting test results:
Initial evaluation loss on 1k subset of HuggingFaceTB/cosmopedia-100k dataset was 1.038. (I'm impressed.)
100 steps of LISA training isn't strictly redu... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["Lambent/cosmo-1b-tune-pythontest", "Lambent/cosmo-1b-qlora-pythontest", "Lambent/cosmo-1b-lisa-pythontest", "Lambent/cosmo-1b-galore-pythontest", "HuggingFaceTB/cosmo-1b"]} | Lambent/cosmo-1b-stock-pythontest | null | [
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"base_model:Lambent/cosmo-1b-galore-pythontest",
"ba... | null | 2024-04-16T17:44:09+00:00 | [
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#transformers #safetensors #llama #text-generation #mergekit #merge #arxiv-2403.19522 #base_model-Lambent/cosmo-1b-tune-pythontest #base_model-Lambent/cosmo-1b-qlora-pythontest #base_model-Lambent/cosmo-1b-lisa-pythontest #base_model-Lambent/cosmo-1b-galore-pythontest #base_model-HuggingFaceTB/cosmo-1b #license-ap... | # pythontestmerge
This is a merge of pre-trained language models created using mergekit.
Catastrophic forgetting test results:
Initial evaluation loss on 1k subset of HuggingFaceTB/cosmopedia-100k dataset was 1.038. (I'm impressed.)
100 steps of LISA training isn't strictly reducing this over time, it's reducing bu... | [
"# pythontestmerge\n\nThis is a merge of pre-trained language models created using mergekit.\n\nCatastrophic forgetting test results:\n\nInitial evaluation loss on 1k subset of HuggingFaceTB/cosmopedia-100k dataset was 1.038. (I'm impressed.)\n\n100 steps of LISA training isn't strictly reducing this over time, it'... | [
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text-generation | transformers |
# WizardLM-2-4x7B-MoE
WizardLM-2-4x7B-MoE is an experimental MoE model made with [Mergekit](https://github.com/arcee-ai/mergekit). It was made by combining four [WizardLM-2-7B](https://huggingface.co/microsoft/WizardLM-2-7B) models using the random gate mode.
Please be sure to set experts per token to 4 for the bes... | {"license": "apache-2.0", "tags": ["MoE", "merge", "mergekit", "Mistral", "Microsoft/WizardLM-2-7B"]} | Skylaude/WizardLM-2-4x7B-MoE | null | [
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#transformers #safetensors #mixtral #text-generation #MoE #merge #mergekit #Mistral #Microsoft/WizardLM-2-7B #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# WizardLM-2-4x7B-MoE
WizardLM-2-4x7B-MoE is an experimental MoE model made with Mergekit. It was made by combining four WizardLM-2-7B models using the random gate mode.
Please be sure to set experts per token to 4 for the best results! Context length should be the same as Mistral-7B-Instruct-v0.1 (8k tokens). For ... | [
"# WizardLM-2-4x7B-MoE\n\nWizardLM-2-4x7B-MoE is an experimental MoE model made with Mergekit. It was made by combining four WizardLM-2-7B models using the random gate mode. \n\nPlease be sure to set experts per token to 4 for the best results! Context length should be the same as Mistral-7B-Instruct-v0.1 (8k token... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_mouse_2-seqsight_16384_512_56M-L32_all
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_mouse_2-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_mouse_2-seqsight_16384_512_56M-L32_all | null | [
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"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\_mouse\_2-seqsight\_16384\_512\_56M-L32\_all
================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_mouse\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3006
* F1 Score: 0.80... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | doxgxxn/gemma_prompt_recovery | 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": []} | Kastanie99/zephyr-7b-beta-req-haoran-mt-16042024 | null | [
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# Model Card for Model ID
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ruBert-base-sberquad-0.02-len_3-filtered
This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/a... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "ai-forever/ruBert-base", "model-index": [{"name": "ruBert-base-sberquad-0.02-len_3-filtered", "results": []}]} | Shalazary/ruBert-base-sberquad-0.02-len_3-filtered | null | [
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"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:ai-forever/ruBert-base",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T17:52:09+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #generated_from_trainer #base_model-ai-forever/ruBert-base #license-apache-2.0 #region-us
|
# ruBert-base-sberquad-0.02-len_3-filtered
This model is a fine-tuned version of ai-forever/ruBert-base on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axo... | {"license": "gemma", "library_name": "peft", "tags": ["axolotl", "generated_from_trainer"], "base_model": "google/gemma-2b", "model-index": [{"name": "gemma_odia_2b_v1", "results": []}]} | sam2ai/gemma_odia_2b_v1 | null | [
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| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
gemma\_odia\_2b\_v1
===================
This model is a fine-tuned version of google/gemma-2b on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 3.2357
Model desc... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 8\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 128\... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_splice_reconstructed-seqsight_16384_512_56M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_16384_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_16384_512_56M", "model-index": [{"name": "GUE_splice_reconstructed-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_splice_reconstructed-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T17:54:31+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_splice\_reconstructed-seqsight\_16384\_512\_56M-L32\_all
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_splice\_reconstructed dataset.
It achieves the following results on the evaluation... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
... | {"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]} | NugentMichael/ppo-Huggy | null | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | null | 2024-04-16T17:55:55+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us
|
# ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* where you te... | [
"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutorial* wh... | [
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"# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n W... | [
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"TAGS\n#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us \n# ppo Agent playing Huggy\n This is a trained model of a ppo agent playing Huggy\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrot... |
text-generation | transformers |
# Spaetzle-v64-7b
Spaetzle-v64-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [flemmingmiguel/NeuDist-Ro-7B](https://huggingface.co/flemmingmiguel/NeuDist-Ro-7B)
* [cstr/Spaetzle-v63-7b](https://huggingface.co/cstr/S... | {"tags": ["merge", "mergekit", "lazymergekit", "flemmingmiguel/NeuDist-Ro-7B", "cstr/Spaetzle-v63-7b", "ResplendentAI/Flora_DPO_7B"], "base_model": ["flemmingmiguel/NeuDist-Ro-7B", "cstr/Spaetzle-v63-7b", "ResplendentAI/Flora_DPO_7B"]} | cstr/Spaetzle-v64-7b | null | [
"transformers",
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"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
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"conversational",
"base_model:flemmingmiguel/NeuDist-Ro-7B",
"base_model:cstr/Spaetzle-v63-7b",
"base_mode... | null | 2024-04-16T17:57:06+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #flemmingmiguel/NeuDist-Ro-7B #cstr/Spaetzle-v63-7b #ResplendentAI/Flora_DPO_7B #conversational #base_model-flemmingmiguel/NeuDist-Ro-7B #base_model-cstr/Spaetzle-v63-7b #base_model-ResplendentAI/Flora_DPO_7B #autotrain_compatible ... |
# Spaetzle-v64-7b
Spaetzle-v64-7b is a merge of the following models using LazyMergekit:
* flemmingmiguel/NeuDist-Ro-7B
* cstr/Spaetzle-v63-7b
* ResplendentAI/Flora_DPO_7B
## Configuration
## Usage
| [
"# Spaetzle-v64-7b\n\nSpaetzle-v64-7b is a merge of the following models using LazyMergekit:\n* flemmingmiguel/NeuDist-Ro-7B\n* cstr/Spaetzle-v63-7b\n* ResplendentAI/Flora_DPO_7B",
"## Configuration",
"## Usage"
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small GA-EN Speech Translation
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/opena... | {"language": ["ga", "en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ymoslem/IWSLT2023-GA-EN", "ymoslem/FLEURS-GA-EN", "ymoslem/BitesizeIrish-GA-EN", "ymoslem/SpokenWords-GA-EN-MTed", "ymoslem/Tatoeba-Speech-Irish", "ymoslem/Wikimedia-Speech-Irish"], "metrics": ["bleu", "wer"], "base_mo... | ymoslem/whisper-small-ga2en-v3.1 | null | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"ga",
"en",
"dataset:ymoslem/IWSLT2023-GA-EN",
"dataset:ymoslem/FLEURS-GA-EN",
"dataset:ymoslem/BitesizeIrish-GA-EN",
"dataset:ymoslem/SpokenWords-GA-EN-MTed",
"dataset:ymoslem/... | null | 2024-04-16T17:58:43+00:00 | [] | [
"ga",
"en"
] | TAGS
#transformers #tensorboard #safetensors #whisper #automatic-speech-recognition #generated_from_trainer #ga #en #dataset-ymoslem/IWSLT2023-GA-EN #dataset-ymoslem/FLEURS-GA-EN #dataset-ymoslem/BitesizeIrish-GA-EN #dataset-ymoslem/SpokenWords-GA-EN-MTed #dataset-ymoslem/Tatoeba-Speech-Irish #dataset-ymoslem/Wikimedia... | Whisper Small GA-EN Speech Translation
======================================
This model is a fine-tuned version of openai/whisper-small on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset.
The best model checkpoint (this version) based on ChrF is at step 2000, epoch 1.31, and it achieves... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\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* lr\\_scheduler\\_warmup\\_step... | [
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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. -->
# finetuning-sentiment-model-bert-base-uncased-ALL-SAMPLES-4-epochs
This model is a fine-tuned version of [bert-base-uncased](http... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "bert-base-uncased", "model-index": [{"name": "finetuning-sentiment-model-bert-base-uncased-ALL-SAMPLES-4-epochs", "results": []}]} | AndreiUrsu/finetuning-sentiment-model-bert-base-uncased-ALL-SAMPLES-4-epochs | null | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:bert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T18:00:34+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# finetuning-sentiment-model-bert-base-uncased-ALL-SAMPLES-4-epochs
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: 0.3288
- Accuracy: 0.9392
- F1: 0.9402
## Model description
More information needed
## Intended uses ... | [
"# finetuning-sentiment-model-bert-base-uncased-ALL-SAMPLES-4-epochs\n\nThis model is a fine-tuned version of bert-base-uncased on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.3288\n- Accuracy: 0.9392\n- F1: 0.9402",
"## Model description\n\nMore information needed",
... | [
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text-generation | null |
# NikolayKozloff/CodeQwen1.5-7B-Q8_0-GGUF
This model was converted to GGUF format from [`Qwen/CodeQwen1.5-7B`](https://huggingface.co/Qwen/CodeQwen1.5-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.... | {"language": ["en"], "license": "other", "tags": ["pretrained", "llama-cpp", "gguf-my-repo"], "license_name": "tongyi-qianwen-research", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B/blob/main/LICENSE", "pipeline_tag": "text-generation"} | NikolayKozloff/CodeQwen1.5-7B-Q8_0-GGUF | null | [
"gguf",
"pretrained",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"license:other",
"region:us"
] | null | 2024-04-16T18:01:58+00:00 | [] | [
"en"
] | TAGS
#gguf #pretrained #llama-cpp #gguf-my-repo #text-generation #en #license-other #region-us
|
# NikolayKozloff/CodeQwen1.5-7B-Q8_0-GGUF
This model was converted to GGUF format from 'Qwen/CodeQwen1.5-7B' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
Not... | [
"# NikolayKozloff/CodeQwen1.5-7B-Q8_0-GGUF\nThis model was converted to GGUF format from 'Qwen/CodeQwen1.5-7B' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL server or the CLI.\n\nCLI:... | [
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text-generation | transformers |
# Hermetic-Llama-Ties
Hermetic-Llama-Ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [BEE-spoke-data/smol_llama-220M-openhermes](https://huggingface.co/BEE-spoke-data/smol_llama-220M-openhermes)
* [BEE-spoke-data/sm... | {"tags": ["merge", "mergekit", "lazymergekit", "BEE-spoke-data/smol_llama-220M-openhermes", "BEE-spoke-data/smol_llama-220M-GQA"], "base_model": ["BEE-spoke-data/smol_llama-220M-openhermes", "BEE-spoke-data/smol_llama-220M-GQA"]} | JoPmt/Hermetic-Llama-Ties | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"BEE-spoke-data/smol_llama-220M-openhermes",
"BEE-spoke-data/smol_llama-220M-GQA",
"base_model:BEE-spoke-data/smol_llama-220M-openhermes",
"base_model:BEE-spoke-data/smol_llama-220M-GQA",
"autotrain... | null | 2024-04-16T18:02:55+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #merge #mergekit #lazymergekit #BEE-spoke-data/smol_llama-220M-openhermes #BEE-spoke-data/smol_llama-220M-GQA #base_model-BEE-spoke-data/smol_llama-220M-openhermes #base_model-BEE-spoke-data/smol_llama-220M-GQA #autotrain_compatible #endpoints_compatible #text-gen... |
# Hermetic-Llama-Ties
Hermetic-Llama-Ties is a merge of the following models using LazyMergekit:
* BEE-spoke-data/smol_llama-220M-openhermes
* BEE-spoke-data/smol_llama-220M-GQA
## Configuration
## Usage
| [
"# Hermetic-Llama-Ties\n\nHermetic-Llama-Ties is a merge of the following models using LazyMergekit:\n* BEE-spoke-data/smol_llama-220M-openhermes\n* BEE-spoke-data/smol_llama-220M-GQA",
"## Configuration",
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Symptoms_to_Diagnosis_SonatafyAI_BERT_v1
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-b... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "widget": [{"text": "The constant thirst and frequent trips to the bathroom were the first signs that something was off. I remember feeling exhausted all the time, even after a full night's sleep. M... | ajtamayoh/Symptoms_to_Diagnosis_SonatafyAI_BERT_v1 | null | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:bert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T18:05:36+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| Symptoms\_to\_Diagnosis\_SonatafyAI\_BERT\_v1
=============================================
This model is a fine-tuned version of bert-base-uncased on the symptoms to diagnosis dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4088
* Accuracy: 0.9387
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Train... | [
"TAGS\n#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learnin... | [
55,
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"TAGS\n#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_ra... |
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. -->
# model_hh_usp3_dpo5
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_usp3_dpo5", "results": []}]} | guoyu-zhang/model_hh_usp3_dpo5 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-16T18:05:51+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_usp3\_dpo5
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.6259
* Rewards/chosen: -6.2124
* Rewards/rejected: -11.7257
* Rewards/accuracies: 0.7200
* Rewards/margins: 5.5132... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\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=... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_0-seqsight_16384_512_56M-L32_all
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_tf_0-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_0-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T18:06:18+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_tf\_0-seqsight\_16384\_512\_56M-L32\_all
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_tf\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6159
* F1 Score: 0.7040
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\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 |
# CodeQwen1.5-7B
AWQ quantized version of CodeQwen1.5-7B model.
---
## Introduction
CodeQwen1.5 is the Code-Specific version of Qwen1.5. It is a transformer-based decoder-only language model pretrained on a large amount of data of codes.
* Strong code generation capabilities and competitve performance across a s... | {"language": ["en"], "license": "other", "tags": ["pretrained"], "license_name": "tongyi-qianwen-research", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B/blob/main/LICENSE", "pipeline_tag": "text-generation"} | TechxGenus/CodeQwen1.5-7B-AWQ | null | [
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"4-bit",
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#transformers #safetensors #qwen2 #text-generation #pretrained #conversational #en #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# CodeQwen1.5-7B
AWQ quantized version of CodeQwen1.5-7B model.
---
## Introduction
CodeQwen1.5 is the Code-Specific version of Qwen1.5. It is a transformer-based decoder-only language model pretrained on a large amount of data of codes.
* Strong code generation capabilities and competitve performance across a s... | [
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"TAGS\n#transformers #safetensors #qwen2 #text-generation #pretrained #conversational #en #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n# CodeQwen1.5-7B\n\nAWQ quantized version of CodeQwen1.5-7B model.\n\n---## Introduction\n\nCodeQwen1.5 is the Code-Spec... |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_1-seqsight_16384_512_56M-L32_all
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_tf_1-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_1-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T18:12:46+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_tf\_1-seqsight\_16384\_512\_56M-L32\_all
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_tf\_1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5163
* F1 Score: 0.7459
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* opti... |
reinforcement-learning | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-CartPole8", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{"t... | erikbritto/Reinforce-Cartpole8 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-16T18:12:47+00:00 | [] | [] | TAGS
#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
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32,
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"TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Lear... |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_4-seqsight_16384_512_56M-L32_all
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_tf_4-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_4-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T18:14:30+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_tf\_4-seqsight\_16384\_512\_56M-L32\_all
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_tf\_4 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3102
* F1 Score: 0.6830
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\n* seed: 42\n* opti... |
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... | gsalmon/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-16T18:15:15+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
null | null | # Meta Llama 3
We are unlocking the power of large language models. Our latest version of Llama is now accessible to individuals, creators, researchers, and businesses of all sizes so that they can experiment, innovate, and scale their ideas responsibly.
This release includes model weights and starting code for pre-tra... | {"language": ["en"], "license": "llama2", "tags": ["facebook", "meta", "pytorch", "llama", "llama-2"], "extra_gated_heading": "You need to share contact information with Meta to access this model", "extra_gated_prompt": "### LLAMA 3 COMMUNITY LICENSE AGREEMENT Meta Llama 3 Version Release Date: April 18, 2024 \"Agreeme... | margaret-test/test-1 | null | [
"facebook",
"meta",
"pytorch",
"llama",
"llama-2",
"en",
"license:llama2",
"region:us"
] | null | 2024-04-16T18:16:27+00:00 | [] | [
"en"
] | TAGS
#facebook #meta #pytorch #llama #llama-2 #en #license-llama2 #region-us
| Meta Llama 3
============
We are unlocking the power of large language models. Our latest version of Llama is now accessible to individuals, creators, researchers, and businesses of all sizes so that they can experiment, innovate, and scale their ideas responsibly.
This release includes model weights and starting cod... | [
"### Access to Hugging Face\n\n\nWe are also providing downloads on Hugging Face.\n\n\nQuick Start\n-----------\n\n\nYou can follow the steps below to quickly get up and running with Llama 3 models. These steps will let you run quick inference locally. For more examples, see the Llama recipes repository.\n\n\n1. In... | [
"TAGS\n#facebook #meta #pytorch #llama #llama-2 #en #license-llama2 #region-us \n",
"### Access to Hugging Face\n\n\nWe are also providing downloads on Hugging Face.\n\n\nQuick Start\n-----------\n\n\nYou can follow the steps below to quickly get up and running with Llama 3 models. These steps will let you run qu... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_3-seqsight_16384_512_56M-L32_all
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_tf_3-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_3-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T18:17:05+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_tf\_3-seqsight\_16384\_512\_56M-L32\_all
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_tf\_3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6507
* F1 Score: 0.6032
* Accu... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 2048\n* eval\\_batch\\_size: 2048\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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object-detection | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# detr
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unkno... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/detr-resnet-50", "model-index": [{"name": "detr", "results": []}]} | maxencerch/detr | null | [
"transformers",
"tensorboard",
"safetensors",
"detr",
"object-detection",
"generated_from_trainer",
"base_model:facebook/detr-resnet-50",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T18:17:10+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #detr #object-detection #generated_from_trainer #base_model-facebook/detr-resnet-50 #license-apache-2.0 #endpoints_compatible #region-us
| detr
====
This model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3326
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\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: 1\n* mixed\\_prec... | [
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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. -->
# tiny-gpt2-github_cybersecurity_READMEs
This model is a fine-tuned version of [sshleifer/tiny-gpt2](https://huggingface.co/sshlei... | {"tags": ["generated_from_trainer"], "base_model": "sshleifer/tiny-gpt2", "model-index": [{"name": "tiny-gpt2-github_cybersecurity_READMEs", "results": []}]} | clarapan/tiny-gpt2-github_cybersecurity_READMEs | null | [
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] | null | 2024-04-16T18:17:24+00:00 | [] | [] | TAGS
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| tiny-gpt2-github\_cybersecurity\_READMEs
========================================
This model is a fine-tuned version of sshleifer/tiny-gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 9.5272
Model description
-----------------
More information needed
Intended uses &... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3.0",
"### Traini... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/saucam/Arithmo-Wizard-2-7B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show ... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lucyknada/microsoft_WizardLM-2-7B", "upaya07/Arithmo2-Mistral-7B"], "base_model": "saucam/Arithmo-Wizard-2-7B", "quantized_by": "mradermacher"} | mradermacher/Arithmo-Wizard-2-7B-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
null | transformers |
# Uploaded model
- **Developed by:** codesagar
- **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/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | codesagar/prompt-guard-classification-v9 | null | [
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|
# Uploaded model
- Developed by: codesagar
- 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 | transformers |
# Uploaded model
- **Developed by:** codesagar
- **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/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | codesagar/prompt-guard-reasoning-v9 | null | [
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|
# Uploaded model
- Developed by: codesagar
- 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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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-PixelCopter", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopter-PL... | minindu-liya99/Reinforce-PixelCopter | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-16T18:22:37+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_tf_2-seqsight_16384_512_56M-L32_all
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_tf_2-seqsight_16384_512_56M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_tf_2-seqsight_16384_512_56M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_16384_512_56M",
"region:us"
] | null | 2024-04-16T18:23:07+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_16384_512_56M #region-us
| GUE\_tf\_2-seqsight\_16384\_512\_56M-L32\_all
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_16384\_512\_56M on the mahdibaghbanzadeh/GUE\_tf\_2 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2019
* F1 Score: 0.6650
* Accu... | [
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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"} | vaarrun009/Rzolut_Mistral_NER_Sentiment | null | [
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"base_model:mistralai/Mistral-7B-Instruct-v0.2",
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"1910.09700"
] | [] | TAGS
#peft #safetensors #arxiv-1910.09700 #base_model-mistralai/Mistral-7B-Instruct-v0.2 #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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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... | b0n541/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
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] | null | 2024-04-16T18:28:09+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
reinforcement-learning | null |
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="MLIsaac/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional att... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | MLIsaac/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-16T18:28:32+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
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] |
text-generation | transformers | # Introduction
The model is primarily designed for translating Fortran code into C++ code. It is based on the deepseek-ai/deepseek-coder-33b-instruct model. Fine-tuned on a customized Fortran to C++ translation dataset.
# Model Inference
The code for inference and Web demo is shown in the github: [Fortran2Cpp](ht... | {"license": "apache-2.0", "tags": ["code"], "pipeline_tag": "text-generation"} | Bin12345/Fortran2Cpp | null | [
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"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T18:29:59+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #code #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Introduction
The model is primarily designed for translating Fortran code into C++ code. It is based on the deepseek-ai/deepseek-coder-33b-instruct model. Fine-tuned on a customized Fortran to C++ translation dataset.
# Model Inference
The code for inference and Web demo is shown in the github: Fortran2Cpp
| [
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null | transformers |
To load the pretrained model:
```
from exlib.datasets.massmaps import MassMapsConvnetRegModel
model = MassMapsConvnetForImageRegression.from_pretrained(f'BrachioLab/massmaps-conv')
``` | {"license": "mit"} | BrachioLab/massmaps-conv | null | [
"transformers",
"pytorch",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T18:32:13+00:00 | [] | [] | TAGS
#transformers #pytorch #license-mit #endpoints_compatible #region-us
|
To load the pretrained model:
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_tata-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_51... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T18:32:16+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_32768\_512\_30M-L32\_all
=============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation... | [
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text-classification | transformers |
Fine-tuned [LVBERT](https://huggingface.co/AiLab-IMCS-UL/lvbert) for multi-label emotion classification task.
Model was trained on [lv_go_emotions](https://huggingface.co/datasets/SkyWater21/lv_go_emotions) dataset. This dataset is Latvian translation of [GoEmotions](https://huggingface.co/datasets/go_emotions) datas... | {"language": ["lv"], "license": "mit", "datasets": ["SkyWater21/lv_go_emotions"]} | SkyWater21/lvbert-lv-go-emotions | null | [
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"region:us"
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"lv"
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| Fine-tuned LVBERT for multi-label emotion classification task.
Model was trained on lv\_go\_emotions dataset. This dataset is Latvian translation of GoEmotions dataset. Google Translate was used to generate the machine translation.
Labels:
Seed used for random number generator is 42:
Training parameters:
Eval... | [] | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="MLIsaac/Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
e... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- ... | MLIsaac/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-16T18:33:51+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
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] |
sentence-similarity | sentence-transformers |
# atasoglu/xlm-roberta-base-nli-stsb-tr
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
This model was adapted from [FacebookAI/xlm-roberta-base](https://huggingface.co... | {"language": ["tr"], "license": "mit", "library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "datasets": ["nli_tr", "emrecan/stsb-mt-turkish"], "pipeline_tag": "sentence-similarity", "base_model": "FacebookAI/xlm-roberta-base"} | atasoglu/xlm-roberta-base-nli-stsb-tr | null | [
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"base_model:FacebookAI/xlm-roberta-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T18:34:12+00:00 | [] | [
"tr"
] | TAGS
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|
# atasoglu/xlm-roberta-base-nli-stsb-tr
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
This model was adapted from FacebookAI/xlm-roberta-base and fine-tuned on these datasets:
- nli_tr
- emre... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-small-pt-1000h
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small)... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["fsicoli/cv17-fleurs-coraa-mls-ted-alcaim-cf-cdc-lapsbm-lapsmail-sydney-lingualibre-voxforge-tatoeba"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "whisper-medium-pt-1000h", "results": [{"task": {"type": "... | fsicoli/whisper-small-pt-1000h | null | [
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... | null | 2024-04-16T18:34:52+00:00 | [] | [] | TAGS
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| whisper-small-pt-1000h
======================
This model is a fine-tuned version of openai/whisper-small on the fsicoli/cv17-fleurs-coraa-mls-ted-alcaim-cf-cdc-lapsbm-lapsmail-sydney-lingualibre-voxforge-tatoeba default dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3036
* Wer: 0.1490
... | [
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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": "stabilityai/stablelm-3b-4e1t"} | AY2324S2-CS4248-Team-47/StableLM-DPO-Backtranslations | null | [
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"1910.09700"
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#peft #safetensors #arxiv-1910.09700 #base_model-stabilityai/stablelm-3b-4e1t #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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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. -->
# leagaleasy-mistral-7b-instruct-v0.2-v1
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggin... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "leagaleasy-mistral-7b-instruct-v0.2-v1", "results": []}]} | philmui/leagaleasy-mistral-7b-instruct-v0.2-v1 | null | [
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|
# leagaleasy-mistral-7b-instruct-v0.2-v1
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training p... | [
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text-classification | adapter-transformers | MFANN chain of thought experiment developed my makhi burroughs.
3b version here: https://huggingface.co/netcat420/MFANN3bv0.4
BENCHMARKS: avg: 72.23 ARC: 68.86 HellaSwag: 86.65 MMLU: 63.63 TruthfulQA: 70.18 winogrande: 79.72 GSM8K: 64.37
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6435f27b2d0e... | {"license": "apache-2.0", "library_name": "adapter-transformers", "datasets": ["netcat420/MFANN"], "pipeline_tag": "text-classification"} | netcat420/MFANNv0.5-GGUF | null | [
"adapter-transformers",
"gguf",
"text-classification",
"dataset:netcat420/MFANN",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T18:36:47+00:00 | [] | [] | TAGS
#adapter-transformers #gguf #text-classification #dataset-netcat420/MFANN #license-apache-2.0 #region-us
| MFANN chain of thought experiment developed my makhi burroughs.
3b version here: URL
BENCHMARKS: avg: 72.23 ARC: 68.86 HellaSwag: 86.65 MMLU: 63.63 TruthfulQA: 70.18 winogrande: 79.72 GSM8K: 64.37
!image/png
!image/png
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - rzhen0615/corgy_dog_LoRA
<Gallery />
## Model description
These are rzhen0615/corgy_dog_LoRA L... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "lora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "a photo of TOK dog", "wi... | rzhen0615/corgy_dog_LoRA | null | [
"diffusers",
"tensorboard",
"text-to-image",
"diffusers-training",
"lora",
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"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
] | null | 2024-04-16T18:37:41+00:00 | [] | [] | TAGS
#diffusers #tensorboard #text-to-image #diffusers-training #lora #template-sd-lora #stable-diffusion-xl #stable-diffusion-xl-diffusers #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - rzhen0615/corgy_dog_LoRA
<Gallery />
## Model description
These are rzhen0615/corgy_dog_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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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. -->
# iter0_full
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbo... | {"license": "apache-2.0", "tags": ["alignment-handbook", "generated_from_trainer"], "datasets": ["UCLA-AGI/SPIN_iter0"], "base_model": "alignment-handbook/zephyr-7b-sft-full", "model-index": [{"name": "iter0_full", "results": []}]} | AmberYifan/test-spin-iter0 | null | [
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"text-genera... | null | 2024-04-16T18:38:05+00:00 | [] | [] | TAGS
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|
# iter0_full
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the UCLA-AGI/SPIN_iter0 dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### T... | [
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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. -->
# model_hh_shp1_dpo7
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_shp1_dpo7", "results": []}]} | guoyu-zhang/model_hh_shp1_dpo7 | null | [
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"safetensors",
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"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
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] | null | 2024-04-16T18:38:32+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_shp1\_dpo7
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.8000
* Rewards/chosen: -7.0133
* Rewards/rejected: -7.1903
* Rewards/accuracies: 0.4800
* Rewards/margins: 0.1770
... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Ppoyaa/Lumina-3.5
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["moe", "frankenmoe", "merge", "mergekit", "lazymergekit"], "base_model": "Ppoyaa/Lumina-3.5", "quantized_by": "mradermacher"} | mradermacher/Lumina-3.5-GGUF | null | [
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"region:us"
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"en"
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#transformers #gguf #moe #frankenmoe #merge #mergekit #lazymergekit #en #base_model-Ppoyaa/Lumina-3.5 #license-apache-2.0 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | ProrabVasili/dqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-16T18:41:54+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-tra... | [
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CNEC_1_1_Supertypes_Czert-B-base-cased
This model is a fine-tuned version of [UWB-AIR/Czert-B-base-cased](https://huggingface.co... | {"tags": ["generated_from_trainer"], "datasets": ["cnec"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "UWB-AIR/Czert-B-base-cased", "model-index": [{"name": "CNEC_1_1_Supertypes_Czert-B-base-cased", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset"... | stulcrad/CNEC_1_1_Supertypes_Czert-B-base-cased | null | [
"transformers",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:cnec",
"base_model:UWB-AIR/Czert-B-base-cased",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T18:45:56+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #token-classification #generated_from_trainer #dataset-cnec #base_model-UWB-AIR/Czert-B-base-cased #model-index #autotrain_compatible #endpoints_compatible #region-us
| CNEC\_1\_1\_Supertypes\_Czert-B-base-cased
==========================================
This model is a fine-tuned version of UWB-AIR/Czert-B-base-cased on the cnec dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2250
* Precision: 0.8262
* Recall: 0.8660
* F1: 0.8457
* Accuracy: 0.9473
M... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 7",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_notata-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T18:48:08+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_32768\_512\_30M-L32\_all
===============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the eval... | [
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... | [
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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": []} | lizashr/mistral-finetuned-pii-masking | null | [
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"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"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... | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_doub... | {"library_name": "peft"} | Inferno0AI/college_model_v1 | null | [
"peft",
"region:us"
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#peft #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_doub... | [
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text-generation | transformers | # Model Card for Mixtral-8x22B
The Mixtral-8x22B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.
For full details of this model please read our [release blog post](https://mistral.ai/news/mixtral-8x22b).
## Warning
This repo contains weights that are compatible with [vLLM](https://git... | {"language": ["fr", "it", "de", "es", "en"], "license": "apache-2.0", "tags": ["moe"]} | mistralai/Mixtral-8x22B-v0.1 | null | [
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"license:apache-2.0",
"autotrain_compatible",
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"region:us"
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#transformers #safetensors #mixtral #text-generation #moe #conversational #fr #it #de #es #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| # Model Card for Mixtral-8x22B
The Mixtral-8x22B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.
For full details of this model please read our release blog post.
## Warning
This repo contains weights that are compatible with vLLM serving of the model as well as Hugging Face transform... | [
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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. -->
# model_hh_usp4_dpo5
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_hh_usp4_dpo5", "results": []}]} | guoyu-zhang/model_hh_usp4_dpo5 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-16T18:58:53+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_usp4\_dpo5
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.9280
* Rewards/chosen: -10.9160
* Rewards/rejected: -14.7692
* Rewards/accuracies: 0.6700
* Rewards/margins: 3.853... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 1\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=... | [
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text-generation | transformers | ARIA V3 has been trained over 100.000 high quality french language with a focus on data bias, grammar and overall language/writing capacities of the model.
The training has been done on Nvidia GPU in the cloud with Amazon Sagemaker.
Base Model : Llama2-70B-Chat-HF
Dataset : private dataset.
Added value : French Lan... | {"license": "other"} | axel-rda/ARIA-70B-V3-4.0bpw-exl2 | null | [
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] | null | 2024-04-16T18:59:31+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| ARIA V3 has been trained over 100.000 high quality french language with a focus on data bias, grammar and overall language/writing capacities of the model.
The training has been done on Nvidia GPU in the cloud with Amazon Sagemaker.
Base Model : Llama2-70B-Chat-HF
Dataset : private dataset.
Added value : French Lan... | [] | [
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] |
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