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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. -->
# bert-petco-text_content-ctr
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google-bert/bert-base-uncased", "model-index": [{"name": "bert-petco-text_content-ctr", "results": []}]} | yimiwang/bert-petco-text_content-ctr | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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#transformers #safetensors #bert #text-classification #generated_from_trainer #base_model-google-bert/bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-petco-text\_content-ctr
============================
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0034
* Mse: 0.0034
* Rmse: 0.0586
* Mae: 0.0408
* R2: 0.4036
* Accuracy: 0.6833
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: 20",
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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-krillin31 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_all-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_core_all-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_core\_all-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\_core\_all dataset.
It achieves the following results on the evaluation... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_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_core_notata-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_notata-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_core\_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\_core\_notata dataset.
It achieves the following results on the e... | [
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text-generation | transformers |
# Gemma-2B-Code-it-Ties
Gemma-2B-Code-it-Ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [mhenrichsen/gemma-2b-it](https://huggingface.co/mhenrichsen/gemma-2b-it)
* [omparghale/gemma-2b-it-code-finetuned](https://hu... | {"tags": ["merge", "mergekit", "lazymergekit", "mhenrichsen/gemma-2b-it", "omparghale/gemma-2b-it-code-finetuned"], "base_model": ["mhenrichsen/gemma-2b-it", "omparghale/gemma-2b-it-code-finetuned"]} | JoPmt/Gemma-2B-Code-it-Ties | null | [
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"base_model:mhenrichsen/gemma-2b-it",
"base_model:omparghale/gemma-2b-it-code-finetuned",
"autotrain_compatible",
"endpoints_com... | null | 2024-04-16T19:10:50+00:00 | [] | [] | TAGS
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|
# Gemma-2B-Code-it-Ties
Gemma-2B-Code-it-Ties is a merge of the following models using LazyMergekit:
* mhenrichsen/gemma-2b-it
* omparghale/gemma-2b-it-code-finetuned
## Configuration
## Usage
| [
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null | null |
# NeuralsynthesisT3q-7B
NeuralsynthesisT3q-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: Kukedlc/NeuralSynthesis-7B-v0.1
- model: chihoonlee10/T3Q-Mistral-... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/NeuralsynthesisT3q-7B | null | [
"merge",
"mergekit",
"lazymergekit",
"automerger",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T19:12:39+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #license-apache-2.0 #region-us
|
# NeuralsynthesisT3q-7B
NeuralsynthesisT3q-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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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. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swin-tiny-patch4-window7-224", "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-eurosat", "results": [{"task": {"type": "image-classification", "name": "Image Clas... | ravipratap366/swin-tiny-patch4-window7-224-finetuned-eurosat | null | [
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"license:apache-2.0",
"model-index",
"autotrain_compatible",
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] | null | 2024-04-16T19:13:43+00:00 | [] | [] | TAGS
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| swin-tiny-patch4-window7-224-finetuned-eurosat
==============================================
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2015
* Accuracy: 0.9358
Model description
------... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_300_all-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_prom_prom_300_all-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_all-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T19:14:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_300\_all-seqsight\_32768\_512\_30M-L32\_all
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_all dataset.
It achieves the following results on the evaluation se... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_prom_prom_core_tata-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_5... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_prom_prom_core_tata-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_tata-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T19:15:01+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_prom\_prom\_core\_tata-seqsight\_32768\_512\_30M-L32\_all
==============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_tata dataset.
It achieves the following results on the evaluat... | [
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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-v01", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopte... | lacknerm/Reinforce-PixelCopter-v01 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
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"model-index",
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#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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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_2_0_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_2_0_Supertypes_Czert-B-base-cased", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset"... | stulcrad/CNEC_2_0_Supertypes_Czert-B-base-cased | null | [
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| CNEC\_2\_0\_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: 0.2429
* Precision: 0.8320
* Recall: 0.8860
* F1: 0.8582
* Accuracy: 0.9590
M... | [
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null | peft | ## Training procedure
### Framework versions
- PEFT 0.4.0
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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": "bigscience/bloom-560m"} | YvanCarre/BLOOM_PREFIX_TUNING_CAUSALLM | null | [
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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]
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K14ac-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_32768_512_30M-L32_all | null | [
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| GUE\_EMP\_H3K14ac-seqsight\_32768\_512\_30M-L32\_all
====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7921
* F1... | [
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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 - Kousha/animated_pikachu_LORA
<Gallery />
## Model description
These are Kousha/animated_pikach... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "dora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "a photo of PIK Pikachu",... | Kousha/animated_pikachu_LORA | null | [
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"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
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#diffusers #tensorboard #text-to-image #diffusers-training #dora #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 - Kousha/animated_pikachu_LORA
<Gallery />
## Model description
These are Kousha/animated_pikachu_LORA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
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text-generation | transformers |
# Zephyr RMU
Zephyr 7B model with hazardous knowledge about biosecurity and cybersecurity "unlearned" using Representation Misdirection for Unlearning (RMU). For more details, please check [our paper](https://arxiv.org/abs/2403.03218).
## Model sources
- Base model: [zephyr-7B-beta](https://huggingface.co/HuggingFa... | {"language": ["en"], "license": "mit", "library_name": "transformers", "datasets": ["cais/wmdp", "cais/wmdp-corpora"], "pipeline_tag": "text-generation", "arxiv": ["arxiv.org/abs/2403.03218"]} | cais/Zephyr_RMU | null | [
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| Zephyr RMU
==========
Zephyr 7B model with hazardous knowledge about biosecurity and cybersecurity "unlearned" using Representation Misdirection for Unlearning (RMU). For more details, please check our paper.
Model sources
-------------
* Base model: zephyr-7B-beta
* Repository: URL
* Website: URL
* Corpora used ... | [] | [
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text-generation | transformers |
# Mixtral 8x7B Instruct RMU
Mixtral 8x7B Instruct model with hazardous knowledge about biosecurity and cybersecurity "unlearned" using Representation Misdirection for Unlearning (RMU). For more details, please check [our paper](https://arxiv.org/abs/2403.03218).
## Model sources
- Base model: [Mixtral-8x7B-Instruct... | {"language": ["en"], "license": "mit", "library_name": "transformers", "datasets": ["cais/wmdp", "cais/wmdp-corpora"], "pipeline_tag": "text-generation", "arxiv": ["arxiv.org/abs/2403.03218"]} | cais/Mixtral-8x7B-Instruct_RMU | null | [
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| Mixtral 8x7B Instruct RMU
=========================
Mixtral 8x7B Instruct model with hazardous knowledge about biosecurity and cybersecurity "unlearned" using Representation Misdirection for Unlearning (RMU). For more details, please check our paper.
Model sources
-------------
* Base model: Mixtral-8x7B-Instruct... | [] | [
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text-generation | transformers |
<img src="./Goku-8x22b-v0.1.webp" alt="Goku 8x22B v0.1 Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Goku-8x22B-v0.2 (Goku 141b-A35b)
A fine-tuned version of [v2ray/Mixtral-8x22B-v0.1](https://huggingface.co/v2ray/Mixtral-8x22B-v0.1) model on the following datasets:
- teknium/... | {"language": ["fr", "it", "de", "es", "en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["moe", "mixtral", "sharegpt", "axolotl"], "datasets": ["MaziyarPanahi/WizardLM_evol_instruct_V2_196k", "microsoft/orca-math-word-problems-200k", "teknium/OpenHermes-2.5"], "model_name": "Goku-8x22B-v0.2", "bas... | MaziyarPanahi/Goku-8x22B-v0.2 | null | [
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<img src="./Goku-8x22b-v0.1.webp" alt="Goku 8x22B v0.1 Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Goku-8x22B-v0.2 (Goku 141b-A35b)
A fine-tuned version of v2ray/Mixtral-8x22B-v0.1 model on the following datasets:
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sentence-similarity | sentence-transformers |
# sbastola/muril-base-cased-sentence-transformer-snli-nepali
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-Tran... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "datasets": ["stanfordnlp/snli"], "pipeline_tag": "sentence-similarity"} | sbastola/muril-base-cased-sentence-transformer-snli-nepali | null | [
"sentence-transformers",
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"bert",
"feature-extraction",
"sentence-similarity",
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"dataset:stanfordnlp/snli",
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"region:us"
] | null | 2024-04-16T19:26:18+00:00 | [] | [] | TAGS
#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #transformers #dataset-stanfordnlp/snli #endpoints_compatible #region-us
|
# sbastola/muril-base-cased-sentence-transformer-snli-nepali
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 sent... | [
"# sbastola/muril-base-cased-sentence-transformer-snli-nepali\n\nThis 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)\n\nUsing this model becomes easy when you... | [
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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).
Testing training data validation:
* Model Stock 3/4 Loss: 0.451
My hypothesis that the pretraining was dragging down the stock merge's performance on training data in any way seems inaccurat... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["HuggingFaceTB/cosmo-1b", "Lambent/cosmo-1b-galore-pythontest", "Lambent/cosmo-1b-qlora-pythontest", "Lambent/cosmo-1b-lisa-pythontest"]} | Lambent/cosmo-1b-stock-pythontest-0.1 | null | [
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"arxiv:2403.19522",
"base_model:HuggingFaceTB/cosmo-1b",
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"autotrain_co... | null | 2024-04-16T19:26:36+00:00 | [
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This is a merge of pre-trained language models created using mergekit.
Testing training data validation:
* Model Stock 3/4 Loss: 0.451
My hypothesis that the pretraining was dragging down the stock merge's performance on training data in any way seems inaccurate.
Cosmopedia data validation:
* Mo... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me2-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_32768_512_30M-L32_all | null | [
"peft",
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T19:26:55+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_32768\_512\_30M-L32\_all
====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6665
* F1... | [
"### 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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null | null | ## Upstream model config
```json
{
"_name_or_path": "output/hermes-llama2-4k/checkpoint-2259",
"architectures": [
"LlamaForCausalLM"
],
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 11008,
"max_position_embeddings... | {"license": "apache-2.0"} | saadnaeem/Llama2-70M-Cosmopedia-100k-Pretrain | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T19:28:42+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
| ## Upstream model config
### Dataset
### Training
### Inference
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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-ties-vjlpsxw
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If the... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "mergekit-community/mergekit-ties-vjlpsxw", "quantized_by": "mradermacher"} | mradermacher/mergekit-ties-vjlpsxw-GGUF | null | [
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"en"
] | TAGS
#transformers #gguf #mergekit #merge #en #base_model-mergekit-community/mergekit-ties-vjlpsxw #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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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_Czert-B-base-cased
This model is a fine-tuned version of [UWB-AIR/Czert-B-base-cased](https://huggingface.co/UWB-AIR/Cz... | {"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_Czert-B-base-cased", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": ... | stulcrad/CNEC_1_1_Czert-B-base-cased | null | [
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"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T19:31:07+00:00 | [] | [] | TAGS
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| CNEC\_1\_1\_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: 0.3330
* Precision: 0.8261
* Recall: 0.8623
* F1: 0.8438
* Accuracy: 0.9410
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: 15",
"### Train... | [
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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": []} | SObryadchikov/t5-large-calculator | null | [
"transformers",
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"t5",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T19:31:15+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #t5 #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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"]} | ulasfiliz954/ppo-Huggy | null | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | null | 2024-04-16T19:31:55+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... | [
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fill-mask | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilroberta-base-finetuned-wikitext2
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilr... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilroberta-base", "model-index": [{"name": "distilroberta-base-finetuned-wikitext2", "results": []}]} | Anwesh0127/distilroberta-base-finetuned-wikitext2 | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"fill-mask",
"generated_from_trainer",
"base_model:distilroberta-base",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T19:32:26+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #fill-mask #generated_from_trainer #base_model-distilroberta-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilroberta-base-finetuned-wikitext2
======================================
This model is a fine-tuned version of distilroberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8611
Model description
-----------------
More information needed
Intended uses & limi... | [
"### 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: 3.0",
"### Traini... | [
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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 - Shen-Wang/rash_img_LoRA
<Gallery />
## Model description
These are Shen-Wang/rash_img_LoRA LoR... | {"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", "text-to-image", "text-to-image", "diffusers-training", "diffusers", "dora", "template:sd-lora", "stabl... | Shen-Wang/rash_img_LoRA | null | [
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"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"dora",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
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#diffusers #text-to-image #diffusers-training #lora #template-sd-lora #stable-diffusion-xl #stable-diffusion-xl-diffusers #dora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - Shen-Wang/rash_img_LoRA
<Gallery />
## Model description
These are Shen-Wang/rash_img_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madeb... | [
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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. -->
# tapt_amazon_helpfulness_classification
This model is a fine-tuned version of [BigTMiami/tapt_helpfulness_base_pretraining_model_... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "BigTMiami/tapt_helpfulness_base_pretraining_model_final", "model-index": [{"name": "tapt_amazon_helpfulness_classification", "results": []}]} | BigTMiami/tapt_amazon_helpfulness_classification | null | [
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"endpoints_compatible",
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] | null | 2024-04-16T19:33:11+00:00 | [] | [] | TAGS
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| tapt\_amazon\_helpfulness\_classification
=========================================
This model is a fine-tuned version of BigTMiami/tapt\_helpfulness\_base\_pretraining\_model\_final on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3873
* Accuracy: 0.87
* F1 Macro: 0.6868
... | [
"### 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=(0.9,0.98) and epsilon=1e-06\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ratio:... | [
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text-classification | transformers | ## Usage
```python
import torch
from informer_models import InformerConfig, InformerForSequenceClassification
model = InformerForSequenceClassification.from_pretrained("BrachioLab/supernova-classification")
model.to(device)
model.eval()
y_true = []
y_pred = []
for i, batch in enumerate(test_dataloader):
print(f"... | {"license": "mit"} | BrachioLab/supernova-classification | null | [
"transformers",
"pytorch",
"informer",
"text-classification",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T19:34:16+00:00 | [] | [] | TAGS
#transformers #pytorch #informer #text-classification #license-mit #autotrain_compatible #endpoints_compatible #region-us
| ## Usage
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text-generation | transformers |
# Spaetzle-v65-7b
Spaetzle-v65-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [yleo/EmertonMonarch-7B](https://huggingface.co/yleo/EmertonMonarch-7B)
## 🧩 Configuration
```yaml
models:
- model: cstr/spaetzle-v62... | {"tags": ["merge", "mergekit", "lazymergekit", "yleo/EmertonMonarch-7B"], "base_model": ["yleo/EmertonMonarch-7B"]} | cstr/Spaetzle-v65-7b | null | [
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"text-generation",
"merge",
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"lazymergekit",
"yleo/EmertonMonarch-7B",
"conversational",
"base_model:yleo/EmertonMonarch-7B",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T19:36:36+00:00 | [] | [] | TAGS
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|
# Spaetzle-v65-7b
Spaetzle-v65-7b is a merge of the following models using LazyMergekit:
* yleo/EmertonMonarch-7B
## Configuration
## Usage
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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. -->
# bert-petco-filtered_fontsize-ctr
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/go... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google-bert/bert-base-uncased", "model-index": [{"name": "bert-petco-filtered_fontsize-ctr", "results": []}]} | yimiwang/bert-petco-filtered_fontsize-ctr | null | [
"transformers",
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"text-classification",
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"base_model:google-bert/bert-base-uncased",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T19:37:49+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #text-classification #generated_from_trainer #base_model-google-bert/bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| bert-petco-filtered\_fontsize-ctr
=================================
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0022
* Mse: 0.0022
* Rmse: 0.0464
* Mae: 0.0364
* R2: 0.4468
* Accuracy: 0.8
Model descrip... | [
"### 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: 20",
"### Train... | [
"TAGS\n#transformers #safetensors #bert #text-classification #generated_from_trainer #base_model-google-bert/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... | [
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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-CartPole-v1", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{... | spietari/Reinforce-CartPole-v1 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-16T19:38:36+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
| [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](h... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T19:39:55+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_32768\_512\_30M-L32\_all
===================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8403
* F1 Sc... | [
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... | [
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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="eulpicard/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional a... | {"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": ... | eulpicard/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-16T19:40:39+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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] |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T19:40:53+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_32768\_512\_30M-L32\_all
====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7726
* F1... | [
"### 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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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H4-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_32768_512_30M-L32_all | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T19:42:40+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4-seqsight\_32768\_512\_30M-L32\_all
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0459
* F1 Score: 0.7342
... | [
"### 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 | peft | # Base Model: mistralai/Mistral-7B-Instruct-v0_2_student_answer_train_examples_mistral_0416
* LoRAs weights for Mistral-7b-Instruct-v0_2
# Noteworthy changes:
* reduced training hyperparams: epochs=3 (previously 4)
* new training prompt: "Teenager students write in simple sentences.
You are a teenage... | {"language": ["en"], "library_name": "peft", "tags": ["education"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "pipeline_tag": "text-generation"} | ntseng/mistralai_Mistral-7B-Instruct-v0_2_student_answer_train_examples_mistral_0416 | null | [
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] | null | 2024-04-16T19:43:32+00:00 | [] | [
"en"
] | TAGS
#peft #tensorboard #safetensors #education #text-generation #en #base_model-mistralai/Mistral-7B-Instruct-v0.2 #region-us
| # Base Model: mistralai/Mistral-7B-Instruct-v0_2_student_answer_train_examples_mistral_0416
* LoRAs weights for Mistral-7b-Instruct-v0_2
# Noteworthy changes:
* reduced training hyperparams: epochs=3 (previously 4)
* new training prompt: "Teenager students write in simple sentences.
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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_2_0_Czert-B-base-cased
This model is a fine-tuned version of [UWB-AIR/Czert-B-base-cased](https://huggingface.co/UWB-AIR/Cz... | {"tags": ["generated_from_trainer"], "datasets": ["cnec"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "UWB-AIR/Czert-B-base-cased", "model-index": [{"name": "CNEC_2_0_Czert-B-base-cased", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": ... | stulcrad/CNEC_2_0_Czert-B-base-cased | null | [
"transformers",
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"token-classification",
"generated_from_trainer",
"dataset:cnec",
"base_model:UWB-AIR/Czert-B-base-cased",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T19:45:15+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\_2\_0\_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: 0.3352
* Precision: 0.8093
* Recall: 0.8548
* F1: 0.8314
* Accuracy: 0.9446
Model description
-------... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](https... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3-seqsight_32768_512_30M-L32_all | null | [
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| GUE\_EMP\_H3-seqsight\_32768\_512\_30M-L32\_all
===============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0191
* F1 Score: 0.7354
... | [
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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-v10 | null | [
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null | transformers |
# Uploaded model
- **Developed by:** codesagar
- **License:** apache-2.0
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[<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-v10 | null | [
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null | null |
# Gemma-2B-Code-Ties-it
Gemma-2B-Code-Ties-it is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [mhenrichsen/gemma-2b-it](https://huggingface.co/mhenrichsen/gemma-2b-it)
* [omparghale/gemma-2b-it-code-finetuned](https://hu... | {"tags": ["merge", "mergekit", "lazymergekit", "mhenrichsen/gemma-2b-it", "omparghale/gemma-2b-it-code-finetuned"], "base_model": ["mhenrichsen/gemma-2b-it", "omparghale/gemma-2b-it-code-finetuned"]} | JoPmt/Gemma-2B-Code-Ties-it | null | [
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|
# Gemma-2B-Code-Ties-it
Gemma-2B-Code-Ties-it is a merge of the following models using LazyMergekit:
* mhenrichsen/gemma-2b-it
* omparghale/gemma-2b-it-code-finetuned
## Configuration
## Usage
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fill-mask | 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": []} | yzimmermann/ChemBERTa-77M-MLM-safetensors | 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. -->
# model_hh_usp1_dpo9
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_usp1_dpo9", "results": []}]} | guoyu-zhang/model_hh_usp1_dpo9 | null | [
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| model\_hh\_usp1\_dpo9
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.
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* Loss: 2.5218
* Rewards/chosen: 4.1305
* Rewards/rejected: -4.5499
* Rewards/accuracies: 0.6900
* Rewards/margins: 8.6805
*... | [
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summarization | transformers | # BART (large-sized model), fine-tuned on scientific_papers
BART Lecture Summarization is a model fine-tuned to summarize lectures, utilizing a dataset of scientific papers due to its similarity in content structure to lectures.
The model employs a custom summarization function tailored specifically for lecture conten... | {"language": ["en"], "license": "mit", "datasets": ["scientific_papers"], "pipeline_tag": "summarization"} | MariamMounnir/Bart_SP | null | [
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| # BART (large-sized model), fine-tuned on scientific_papers
BART Lecture Summarization is a model fine-tuned to summarize lectures, utilizing a dataset of scientific papers due to its similarity in content structure to lectures.
The model employs a custom summarization function tailored specifically for lecture conten... | [
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text2text-generation | 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. -->
# DoubelT/mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-sm... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "google/mt5-small", "model-index": [{"name": "DoubelT/mt5-small-finetuned-amazon-en-es", "results": []}]} | DoubelT/mt5-small-finetuned-amazon-en-es | null | [
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| DoubelT/mt5-small-finetuned-amazon-en-es
========================================
This model is a fine-tuned version of google/mt5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.0094
* Validation Loss: 0.0004
* Epoch: 3
Model description
-----------------
M... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<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": "gemma2b-hotpotqa_uncertain-v1", "results": []}]} | Harsh1729/gemma2b-hotpotqa_uncertain-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'
gemma2b-hotpotqa\_uncertain-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:
* Los... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: 5... | [
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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. -->
# sft-facebook-opt350m-with-own-piidata
This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "facebook/opt-350m", "model-index": [{"name": "sft-facebook-opt350m-with-own-piidata", "results": []}]} | acram/sft-facebook-opt350m-with-own-piidata | null | [
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#peft #safetensors #trl #sft #generated_from_trainer #base_model-facebook/opt-350m #license-other #region-us
|
# sft-facebook-opt350m-with-own-piidata
This model is a fine-tuned version of facebook/opt-350m on the pii_ner_instruction_fine_tuning dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Traini... | [
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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"} | showvikdbz/Enlighten_Instruct | null | [
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#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:
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- License:
- Finetuned from model [optional]:
### Model Sources [optional]
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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. -->
# ConvNeXT_AI_image_detector
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "ConvNeXT_AI_image_detector", "results": []}]} | mmanikanta/ConvNeXT_AI_image_detector | null | [
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#transformers #pytorch #tensorboard #convnext #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| ConvNeXT\_AI\_image\_detector
=============================
This model is a fine-tuned version of facebook/convnext-tiny-224 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0518
* Accuracy: 0.9826
Model description
-----------------
More information needed
Intended us... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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text-generation | transformers |
# Gophos - Sophos Log Interpreter - Gemma 2B-IT Fine-tuned Model
## Overview
This repository contains a fine-tuned version of the Gemma 2B-IT model, tailored specifically for interpreting Sophos logs exported from Splunk. The model is hosted on Hugging Face for easy integration and usage in various applications requi... | {} | SadokBarbouche/gophos | null | [
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|
# Gophos - Sophos Log Interpreter - Gemma 2B-IT Fine-tuned Model
## Overview
This repository contains a fine-tuned version of the Gemma 2B-IT model, tailored specifically for interpreting Sophos logs exported from Splunk. The model is hosted on Hugging Face for easy integration and usage in various applications requi... | [
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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-negative
This model is a fine-tuned version of [ai-forever/ruBert-base](https://hugging... | {"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-negative", "results": []}]} | Shalazary/ruBert-base-sberquad-0.02-len_3-filtered-negative | null | [
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|
# ruBert-base-sberquad-0.02-len_3-filtered-negative
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 proce... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4ac-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](htt... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H4ac-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4ac-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
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"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H4ac-seqsight\_32768\_512\_30M-L32\_all
=================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H4ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8276
* F1 Score: 0... | [
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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. -->
# tapt_helpfulness_unipelt_pretraining_model
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "roberta-base", "model-index": [{"name": "tapt_helpfulness_unipelt_pretraining_model", "results": []}]} | ltuzova/tapt_helpfulness_unipelt_pretraining_model | null | [
"tensorboard",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
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#tensorboard #generated_from_trainer #base_model-roberta-base #license-mit #region-us
| tapt\_helpfulness\_unipelt\_pretraining\_model
==============================================
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.5302
Model description
-----------------
More information needed
Intended u... | [
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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": []} | karsar/Gemma2B_finetune | null | [
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# Model Card for Model ID
## Model Details
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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. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axo... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "out", "results": []}]} | rachfop/mistral-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'
out
===
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9125
Model description
--------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-06\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 32\n*... | [
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fill-mask | 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": []} | yzimmermann/ChemBERTa-zinc-base-v1-safetensors | 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]:
- Model type:
- Language(s) (NLP):
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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. -->
# wav2vec2_lora_7epoch
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "facebook/wav2vec2-base-960h", "model-index": [{"name": "wav2vec2_lora_7epoch", "results": []}]} | Chijioke-Mgbahurike/wav2vec2_lora_7epoch | null | [
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"wav2vec2",
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"license:apache-2.0",
"region:us"
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#peft #tensorboard #safetensors #wav2vec2 #generated_from_trainer #base_model-facebook/wav2vec2-base-960h #license-apache-2.0 #region-us
|
# wav2vec2_lora_7epoch
This model is a fine-tuned version of facebook/wav2vec2-base-960h on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyper... | [
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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. -->
# remote_sensing_gpt_expt
This model is a fine-tuned version of [bigscience/bloom-1b1](https://huggingface.co/bigscience/bloom-1b1... | {"license": "bigscience-bloom-rail-1.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "bigscience/bloom-1b1", "model-index": [{"name": "remote_sensing_gpt_expt", "results": []}]} | gremlin97/remote_sensing_gpt_expt | null | [
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#peft #tensorboard #safetensors #generated_from_trainer #base_model-bigscience/bloom-1b1 #license-bigscience-bloom-rail-1.0 #region-us
| remote\_sensing\_gpt\_expt
==========================
This model is a fine-tuned version of bigscience/bloom-1b1 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.0859
Model description
-----------------
More information needed
Intended uses & limitations
----------------... | [
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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"]} | b0n541/ppo-Huggy | null | [
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#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... | [
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fill-mask | 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": []} | yzimmermann/ChemBERTa_zinc250k_v2_40k-safetensors | null | [
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"roberta",
"fill-mask",
"arxiv:1910.09700",
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"1910.09700"
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#transformers #safetensors #roberta #fill-mask #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
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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": []} | MikeMpapa/lmd_mmm_tokenizer_tutorial_artist_toy | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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text-generation | transformers |
# Spaetzle-v66-7b
Spaetzle-v66-7b 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-v53-7b](https://huggingface.co/cstr/S... | {"tags": ["merge", "mergekit", "lazymergekit", "flemmingmiguel/NeuDist-Ro-7B", "cstr/Spaetzle-v53-7b", "ResplendentAI/Flora_DPO_7B"], "base_model": ["flemmingmiguel/NeuDist-Ro-7B", "cstr/Spaetzle-v53-7b", "ResplendentAI/Flora_DPO_7B"]} | cstr/Spaetzle-v66-7b | null | [
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"base_mode... | null | 2024-04-16T20:04:56+00:00 | [] | [] | TAGS
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# Spaetzle-v66-7b
Spaetzle-v66-7b is a merge of the following models using LazyMergekit:
* flemmingmiguel/NeuDist-Ro-7B
* cstr/Spaetzle-v53-7b
* ResplendentAI/Flora_DPO_7B
## Configuration
## Usage
| [
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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. -->
# distilhubert-finetuned-birdclef
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["birdclef/hubert"], "metrics": ["accuracy"], "base_model": "ntu-spml/distilhubert", "model-index": [{"name": "distilhubert-finetuned-birdclef", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"n... | nmks/distilhubert-finetuned-birdclef | null | [
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| distilhubert-finetuned-birdclef
===============================
This model is a fine-tuned version of ntu-spml/distilhubert on the Birdclef 2024 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8592
* Accuracy: 0.6975
* F1 Macro: 0.4507
* F1 Weighted: 0.6871
Model description
----------... | [
"### 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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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": []} | kssumanth6/t5_small_chit_chat_generator_v2 | null | [
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"1910.09700"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
# Model Card for Mixtral-8x22B-Instruct-v0.1
The Mixtral-8x22B-Instruct-v0.1 Large Language Model (LLM) is an instruct fine-tuned version of the [Mixtral-8x22B-v0.1](https://huggingface.co/mistralai/Mixtral-8x22B-v0.1).
## Run the model
```python
from transformers import AutoModelForCausalLM
from mistral_common.prot... | {"language": ["en", "es", "it", "de", "fr"], "license": "apache-2.0"} | mistralai/Mixtral-8x22B-Instruct-v0.1 | null | [
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|
# Model Card for Mixtral-8x22B-Instruct-v0.1
The Mixtral-8x22B-Instruct-v0.1 Large Language Model (LLM) is an instruct fine-tuned version of the Mixtral-8x22B-v0.1.
## Run the model
Alternatively, you can run this example with the Hugging Face tokenizer.
To use this example, you'll need transformers version 4.39.0 ... | [
"# Model Card for Mixtral-8x22B-Instruct-v0.1\nThe Mixtral-8x22B-Instruct-v0.1 Large Language Model (LLM) is an instruct fine-tuned version of the Mixtral-8x22B-v0.1.",
"## Run the model \n\nAlternatively, you can run this example with the Hugging Face tokenizer.\nTo use this example, you'll need transformers ver... | [
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feature-extraction | 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": []} | hxuanc/bert-base-uncased | null | [
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"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #bert #feature-extraction #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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text-generation | transformers | # MeowGPT Readme
## Overview
MeowGPT, developed by CutyCat2000x, is a language model based on Llama with the checkpoint version 3.5. This model is designed to generate text in a conversational manner and can be used for various natural language processing tasks.
## Usage
### Loading the Model
To use MeowGPT, you can ... | {"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["freeai", "conversational", "meowgpt", "gpt", "free", "opensource", "splittic", "ai"], "pipeline_tag": "text-generation", "widget": [{"text": "<s> [|User|] Hello World </s>[|Assistant|]"}]} | cutycat2000x/MeowGPT-3.5 | null | [
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| # MeowGPT Readme
## Overview
MeowGPT, developed by CutyCat2000x, is a language model based on Llama with the checkpoint version 3.5. This model is designed to generate text in a conversational manner and can be used for various natural language processing tasks.
## Usage
### Loading the Model
To use MeowGPT, you can ... | [
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"## Overview\nMeowGPT, developed by CutyCat2000x, is a language model based on Llama with the checkpoint version 3.5. This model is designed to generate text in a conversational manner and can be used for various natural language processing tasks.",
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text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 8.0bpw
This is a 8.0bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_8.0bpw | null | [
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"8-bit",
"region:us"
] | null | 2024-04-16T20:15:53+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| CodeQwen1.5-7B-Chat - EXL2 8.0bpw
=================================
This is a 8.0bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us \n",
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n... | [
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text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 7.0bpw
This is a 7.0bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_7.0bpw | null | [
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"license:other",
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"text-generation-inference",
"7-bit",
"region:us"
] | null | 2024-04-16T20:17:11+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #7-bit #region-us
| CodeQwen1.5-7B-Chat - EXL2 7.0bpw
=================================
This is a 7.0bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
] | [
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"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n... | [
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text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 6.0bpw
This is a 6.0bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_6.0bpw | null | [
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#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #6-bit #region-us
| CodeQwen1.5-7B-Chat - EXL2 6.0bpw
=================================
This is a 6.0bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
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text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 5.0bpw
This is a 5.0bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_5.0bpw | null | [
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"5-bit",
"region:us"
] | null | 2024-04-16T20:19:27+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #5-bit #region-us
| CodeQwen1.5-7B-Chat - EXL2 5.0bpw
=================================
This is a 5.0bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #5-bit #region-us \n",
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n... | [
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"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #5-bit #region-us \n### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQu... |
text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 4.0bpw
This is a 4.0bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_4.0bpw | null | [
"transformers",
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"text-generation",
"exl2",
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"conversational",
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"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-16T20:20:19+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| CodeQwen1.5-7B-Chat - EXL2 4.0bpw
=================================
This is a 4.0bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n",
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n... | [
73,
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"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQu... |
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": []} | Lugaborg/WaterBug | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T20:20:58+00:00 | [
"1910.09700"
] | [] | TAGS
#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.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s)... | [
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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. -->
# dpo_helpfulhelpful_gpt3_gamma0.0_beta0.1_subset20000_modelmistral7b_maxsteps5000_bz8_lr5e-06
This model is a fine-tuned version ... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "dpo_helpfulhelpful_gpt3_gamma0.0_beta0.1_subset20000_modelmistral7b_maxsteps5000_bz8_lr5e-06", "results": []}]} | Holarissun/dpo_helpfulhelpful_gpt3_gamma0.0_beta0.1_subset20000_modelmistral7b_maxsteps5000_bz8_lr5e-06 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T20:21:05+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-mistralai/Mistral-7B-v0.1 #license-apache-2.0 #region-us
|
# dpo_helpfulhelpful_gpt3_gamma0.0_beta0.1_subset20000_modelmistral7b_maxsteps5000_bz8_lr5e-06
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation da... | [
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"## Intended uses & limitations\n\nMore information needed",
"## Traini... | [
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fill-mask | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# dapt_plus_tapt_helpfulness_base_pretraining_model
This model is a fine-tuned version of [BigTMiami/amazon_pretraining_5M_model_c... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "BigTMiami/amazon_pretraining_5M_model_corrected", "model-index": [{"name": "dapt_plus_tapt_helpfulness_base_pretraining_model", "results": []}]} | BigTMiami/dapt_plus_tapt_helpfulness_base_pretraining_model | null | [
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"license:mit",
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| dapt\_plus\_tapt\_helpfulness\_base\_pretraining\_model
=======================================================
This model is a fine-tuned version of BigTMiami/amazon\_pretraining\_5M\_model\_corrected on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4446
Model description... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 21\n* eval\\_batch\\_size: 21\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 42\n* optimizer: Adam with betas=(0.9,0.98) and epsilon... | [
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text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 3.5bpw
This is a 3.5bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_3.5bpw | null | [
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"qwen2",
"text-generation",
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"license:other",
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] | null | 2024-04-16T20:21:08+00:00 | [] | [
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] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| CodeQwen1.5-7B-Chat - EXL2 3.5bpw
=================================
This is a 3.5bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K79me3-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M]... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K79me3-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K79me3-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T20:21:48+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K79me3-seqsight\_32768\_512\_30M-L32\_all
=====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K79me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6137
*... | [
"### 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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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. -->
# question_generation_final
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown datase... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "t5-small", "model-index": [{"name": "question_generation_final", "results": []}]} | nadika/question_generation_final | null | [
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"t5",
"text2text-generation",
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"license:apache-2.0",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T20:22:07+00:00 | [] | [] | TAGS
#transformers #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-t5-small #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# question_generation_final
This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0602
- eval_runtime: 301.5563
- eval_samples_per_second: 35.051
- eval_steps_per_second: 2.192
- epoch: 0.64
- step: 3500
## Model description
M... | [
"# question_generation_final\n\nThis model is a fine-tuned version of t5-small on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.0602\n- eval_runtime: 301.5563\n- eval_samples_per_second: 35.051\n- eval_steps_per_second: 2.192\n- epoch: 0.64\n- step: 3500",
"## Model... | [
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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": []} | Lugaborg/Procyote | null | [
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"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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"1910.09700"
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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.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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translation | null |
# Model Summary
Based on the pre-quantized Gemma-7B model, this model has been fine-tuned on the Gemma-7B base model for Hinglish/English translations and completions using QLoRA. The training data includes two datasets: fnnerd/Baatcheet_Hinglish_English_Translation_Corpus and findnitai/english-to-hinglish.
This mode... | {"language": ["en", "hi"], "license": "apache-2.0", "tags": ["hindi", "hinglish", "language", "translation"], "datasets": ["fnnerd/Baatcheet_Hinglish_English_Translation_Corpus", "findnitai/english-to-hinglish"], "base_model": "unsloth/gemma-7b-bnb-4bit"} | fnnerd/Baatcheet-7b | null | [
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"hinglish",
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"base_model:unsloth/gemma-7b-bnb-4bit",
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"en",
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#safetensors #hindi #hinglish #language #translation #en #hi #dataset-fnnerd/Baatcheet_Hinglish_English_Translation_Corpus #dataset-findnitai/english-to-hinglish #base_model-unsloth/gemma-7b-bnb-4bit #license-apache-2.0 #region-us
|
# Model Summary
Based on the pre-quantized Gemma-7B model, this model has been fine-tuned on the Gemma-7B base model for Hinglish/English translations and completions using QLoRA. The training data includes two datasets: fnnerd/Baatcheet_Hinglish_English_Translation_Corpus and findnitai/english-to-hinglish.
This mode... | [
"# Model Summary\n\nBased on the pre-quantized Gemma-7B model, this model has been fine-tuned on the Gemma-7B base model for Hinglish/English translations and completions using QLoRA. The training data includes two datasets: fnnerd/Baatcheet_Hinglish_English_Translation_Corpus and findnitai/english-to-hinglish.\nTh... | [
"TAGS\n#safetensors #hindi #hinglish #language #translation #en #hi #dataset-fnnerd/Baatcheet_Hinglish_English_Translation_Corpus #dataset-findnitai/english-to-hinglish #base_model-unsloth/gemma-7b-bnb-4bit #license-apache-2.0 #region-us \n",
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null | mlx |
# GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0) for more details on the model.
## Use with m... | {"license": "apache-2.0", "tags": ["mlx"]} | GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-16T20:27:59+00:00 | [] | [] | TAGS
#mlx #safetensors #qwen2 #license-apache-2.0 #region-us
|
# GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0-mlx\nThis quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0']().\nRefer to the original model card for more details on the model.",
"## Use with mlx"
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"TAGS\n#mlx #safetensors #qwen2 #license-apache-2.0 #region-us \n# GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0-mlx\nThis quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-32B-Chat-layer-mix-bpw-3.0']().\nRefer to the original model card for more details on the model.## Use with mlx"
... |
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": "mit", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "HuggingFaceH4/zephyr-7b-beta", "model-index": [{"name": "model/Featherlite-Aurora-v0.2.1-beta", "results": []}]} | hvadaparty/Featherlite-Aurora-v0.2.1-beta | null | [
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"license:mit",
"4-bit",
"region:us"
] | null | 2024-04-16T20:28:30+00:00 | [] | [] | TAGS
#peft #safetensors #mistral #generated_from_trainer #base_model-HuggingFaceH4/zephyr-7b-beta #license-mit #4-bit #region-us
| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
model/Featherlite-Aurora-v0.2.1-beta
====================================
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-beta on the None dataset.
It achieves the following results on th... | [
"### 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* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n*... | [
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text-generation | transformers |
<img src="https://allenai.org/olmo/olmo-7b-animation.gif" alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Model Card for OLMo 7B
<!-- Provide a quick summary of what the model is/does. -->
OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the sc... | {"language": ["en"], "license": "apache-2.0", "datasets": ["allenai/dolma"]} | monology/olmo-git | null | [
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"dataset:allenai/dolma",
"arxiv:2402.00838",
"arxiv:2302.13971",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-16T20:29:07+00:00 | [
"2402.00838",
"2302.13971"
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"en"
] | TAGS
#transformers #safetensors #olmo #text-generation #custom_code #en #dataset-allenai/dolma #arxiv-2402.00838 #arxiv-2302.13971 #license-apache-2.0 #autotrain_compatible #region-us
| <img src="URL alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
Model Card for OLMo 7B
======================
OLMo is a series of Open Language Models designed to enable the science of language models.
The OLMo models are trained on the Dolma dataset.
We release all code, ... | [
"### Model Description\n\n\n* Developed by: Allen Institute for AI (AI2)\n* Supported by: Databricks, Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, AMD, CSC (Lumi Supercomputer), UW\n* Model type: a Transformer style autoregressive language model.\n* Language(s) (NLP)... | [
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"TAGS\n#transformers #safetensors #olmo #text-generation #custom_code #en #dataset-allenai/dolma #arxiv-2402.00838 #arxiv-2302.13971 #license-apache-2.0 #autotrain_compatible #region-us \n### Model Description\n\n\n* Developed by: Allen Institute for AI (AI2)\n* Supported by: Databricks, Kempner Institute for the S... |
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_shp1_dpo5
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-... | {"library_name": "peft", "tags": ["trl", "dpo", "generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-chat-hf", "model-index": [{"name": "model_shp1_dpo5", "results": []}]} | guoyu-zhang/model_shp1_dpo5 | null | [
"peft",
"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-16T20:30:33+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_shp1\_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: 2.3217
* Rewards/chosen: -0.2355
* Rewards/rejected: -0.1439
* Rewards/accuracies: 0.5
* Rewards/margins: -0.0916
* Logps/re... | [
"### 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=... | [
"TAGS\n#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #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: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradi... | [
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"TAGS\n#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #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: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_... |
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-v02", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopte... | lacknerm/Reinforce-PixelCopter-v02 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-16T20:31:42+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
| [
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
"TAGS\n#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
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"TAGS\n#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of the De... |
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="eulpicard/q-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.52 +/... | eulpicard/q-Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-16T20:32:06+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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"TAGS\n#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n# Q-Learning Agent playing1 Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n\n ## Usage"
] |
null | transformers |
# LeroyDyer/Mixtral_AI_Cyber_Child-Q4_K_M-GGUF
This model was converted to GGUF format from [`LeroyDyer/Mixtral_AI_Cyber_Child`](https://huggingface.co/LeroyDyer/Mixtral_AI_Cyber_Child) 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 m... | {"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["mergekit", "merge", "llama-cpp", "gguf-my-repo"], "base_model": []} | LeroyDyer/Mixtral_AI_Cyber_Child-Q4 | null | [
"transformers",
"gguf",
"mergekit",
"merge",
"llama-cpp",
"gguf-my-repo",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T20:32:59+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #mergekit #merge #llama-cpp #gguf-my-repo #en #license-mit #endpoints_compatible #region-us
|
# LeroyDyer/Mixtral_AI_Cyber_Child-Q4_K_M-GGUF
This model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_Cyber_Child' 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:... | [
"# LeroyDyer/Mixtral_AI_Cyber_Child-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_Cyber_Child' 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 o... | [
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"TAGS\n#transformers #gguf #mergekit #merge #llama-cpp #gguf-my-repo #en #license-mit #endpoints_compatible #region-us \n# LeroyDyer/Mixtral_AI_Cyber_Child-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_Cyber_Child' using URL via the URL's GGUF-my-repo space.\nRefer to the original ... |
text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 3.0bpw
This is a 3.0bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_3.0bpw | null | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"exl2",
"chat",
"conversational",
"en",
"base_model:Qwen/CodeQwen1.5-7B-Chat",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"3-bit",
"region:us"
] | null | 2024-04-16T20:33:49+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #3-bit #region-us
| CodeQwen1.5-7B-Chat - EXL2 3.0bpw
=================================
This is a 3.0bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #3-bit #region-us \n",
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n... | [
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"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #3-bit #region-us \n### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQu... |
text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 2.75bpw
This is a 2.75bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 ma... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_2.75bpw | null | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"exl2",
"chat",
"conversational",
"en",
"base_model:Qwen/CodeQwen1.5-7B-Chat",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T20:34:25+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| CodeQwen1.5-7B-Chat - EXL2 2.75bpw
==================================
This is a 2.75bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
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"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQua... | [
69,
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"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Det... |
text-generation | transformers |
# CodeQwen1.5-7B-Chat - EXL2 2.5bpw
This is a 2.5bpw EXL2 quant of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
Details about the model can be found at the above model page.
## EXL2 Version
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may ... | {"language": ["en"], "license": "other", "tags": ["exl2", "chat"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE", "pipeline_tag": "text-generation", "base_model": "Qwen/CodeQwen1.5-7B-Chat"} | Dracones/CodeQwen1.5-7B-Chat_exl2_2.5bpw | null | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"exl2",
"chat",
"conversational",
"en",
"base_model:Qwen/CodeQwen1.5-7B-Chat",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-16T20:35:03+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| CodeQwen1.5-7B-Chat - EXL2 2.5bpw
=================================
This is a 2.5bpw EXL2 quant of Qwen/CodeQwen1.5-7B-Chat
Details about the model can be found at the above model page.
EXL2 Version
------------
These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not wo... | [
"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Details\n-------------\n\n\nThis is the script used for quantization."
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"### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQua... | [
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"TAGS\n#transformers #safetensors #qwen2 #text-generation #exl2 #chat #conversational #en #base_model-Qwen/CodeQwen1.5-7B-Chat #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Perplexity Script\n\n\nThis was the script used for perplexity testing.\n\n\nQuant Det... |
sentence-similarity | sentence-transformers |
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 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"} | alexakkol/bge-m3-nowrep | null | [
"sentence-transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"feature-extraction",
"sentence-similarity",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T20:35:34+00:00 | [] | [] | TAGS
#sentence-transformers #tensorboard #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 1024 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 ... | [
"# {MODEL_NAME}\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.",
"## Usage (Sentence-Transformers)\n\nUsing this model becomes easy when you have sentence-transformers installed:\n\n\n\... | [
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text-generation | transformers |
# Spaetzle-v67-7b
Spaetzle-v67-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [cstr/Spaetzle-v53-7b](https://huggingface.co/cstr/Spaetzle-v53-7b)
* [cstr/Spaetzle-v55-7b](https://huggingface.co/cstr/Spaetzle-v55-7b)
... | {"tags": ["merge", "mergekit", "lazymergekit", "cstr/Spaetzle-v53-7b", "cstr/Spaetzle-v55-7b"], "base_model": ["cstr/Spaetzle-v53-7b", "cstr/Spaetzle-v55-7b"]} | cstr/Spaetzle-v67-7b | null | [
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"mistral",
"text-generation",
"merge",
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"lazymergekit",
"cstr/Spaetzle-v53-7b",
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"autotrain_compatible",
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"text-... | null | 2024-04-16T20:41:37+00:00 | [] | [] | TAGS
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|
# Spaetzle-v67-7b
Spaetzle-v67-7b is a merge of the following models using LazyMergekit:
* cstr/Spaetzle-v53-7b
* cstr/Spaetzle-v55-7b
## Configuration
## Usage
| [
"# Spaetzle-v67-7b\n\nSpaetzle-v67-7b is a merge of the following models using LazyMergekit:\n* cstr/Spaetzle-v53-7b\n* cstr/Spaetzle-v55-7b",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me1-seqsight_32768_512_30M-L32_all
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_32768_512_30M](... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_32768_512_30M", "model-index": [{"name": "GUE_EMP_H3K4me1-seqsight_32768_512_30M-L32_all", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me1-seqsight_32768_512_30M-L32_all | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_32768_512_30M",
"region:us"
] | null | 2024-04-16T20:42:14+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_32768_512_30M #region-us
| GUE\_EMP\_H3K4me1-seqsight\_32768\_512\_30M-L32\_all
====================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_32768\_512\_30M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me1 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6628
* F1... | [
"### 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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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_dpo9
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_dpo9", "results": []}]} | guoyu-zhang/model_hh_usp2_dpo9 | null | [
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"safetensors",
"trl",
"dpo",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2024-04-16T20:44:20+00:00 | [] | [] | TAGS
#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #region-us
| model\_hh\_usp2\_dpo9
=====================
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: 2.6846
* Rewards/chosen: -0.5731
* Rewards/rejected: -5.6737
* Rewards/accuracies: 0.6400
* Rewards/margins: 5.1005
... | [
"### 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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"TAGS\n#peft #safetensors #trl #dpo #generated_from_trainer #base_model-meta-llama/Llama-2-7b-chat-hf #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: 4\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_... |
feature-extraction | transformers | # jina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564
## Model Description
jina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564 is a fine-tuned version of BAAI/bge-small-en-v1.5 designed for a specific domain.
## Use Case
This model is designed to support various applications in natural language processing an... | {} | florianhoenicke/jina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564 | null | [
"transformers",
"safetensors",
"bert",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T20:44:28+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #feature-extraction #endpoints_compatible #region-us
| # jina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564
## Model Description
jina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564 is a fine-tuned version of BAAI/bge-small-en-v1.5 designed for a specific domain.
## Use Case
This model is designed to support various applications in natural language processing an... | [
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"## Model Description\n\njina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564 is a fine-tuned version of BAAI/bge-small-en-v1.5 designed for a specific domain.",
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"## Model Description\n\njina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564 is a fine-tuned version of BAAI/bge-small-en-v1.5 designed for a specifi... | [
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"TAGS\n#transformers #safetensors #bert #feature-extraction #endpoints_compatible #region-us \n# jina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564## Model Description\n\njina-website-1-0-1-BAAI_bge-small-en-v1.5-50_9062874564 is a fine-tuned version of BAAI/bge-small-en-v1.5 designed for a specific domain.## ... |
sentence-similarity | sentence-transformers |
# sbastola/muril-base-cased-sentence-transformer-snli-nepali-2
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-Tr... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "datasets": ["stanfordnlp/snli"], "pipeline_tag": "sentence-similarity"} | sbastola/muril-base-cased-sentence-transformer-snli-nepali-2 | null | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"dataset:stanfordnlp/snli",
"endpoints_compatible",
"region:us"
] | null | 2024-04-16T20:46:27+00:00 | [] | [] | TAGS
#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #transformers #dataset-stanfordnlp/snli #endpoints_compatible #region-us
|
# sbastola/muril-base-cased-sentence-transformer-snli-nepali-2
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 se... | [
"# sbastola/muril-base-cased-sentence-transformer-snli-nepali-2\n\nThis 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)\n\nUsing this model becomes easy when y... | [
"TAGS\n#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #transformers #dataset-stanfordnlp/snli #endpoints_compatible #region-us \n",
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