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text-generation | transformers | <!-- markdownlint-disable MD041 -->
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content:... | {"license": "apache-2.0", "model_name": "Solar 10.7B Instruct v1.0", "base_model": "upstage/SOLAR-10.7B-Instruct-v1.0", "inference": false, "model_creator": "upstage", "model_type": "solar", "prompt_template": "### User:\n{prompt}\n\n### Assistant:\n", "quantized_by": "TheBloke"} | dmanary-pronavigator/SOLAR-10.7B-Instruct-v1.0-gptq-8bit-1g-actorder_True | null | [
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|
[[TheBloke's LLM work is generously supported by a grant from [andreessen horowitz (a16z)](URL)](URL to contribute? TheBloke's Patreon page</a></p>
</div>
</div>
<div style=)](URL & support: TheBloke's Discord server</a></p>
</div>
<div style=)
---
Solar 10.7B Instruct v1.0... | [
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text-generation | transformers |
# RogerMerge-12B-MoE
RogerMerge-12B-MoE is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [allknowingroger/MultiverseEx26-7B-slerp](https://huggingface.co/allknowingroger/MultiverseEx26-7B-slerp)
... | {"license": "apache-2.0", "tags": ["moe", "frankenmoe", "merge", "mergekit", "lazymergekit", "allknowingroger/MultiverseEx26-7B-slerp", "allknowingroger/PercivalMelodias-7B-slerp"], "base_model": ["allknowingroger/MultiverseEx26-7B-slerp", "allknowingroger/PercivalMelodias-7B-slerp"]} | allknowingroger/RogerMerge-12B-MoE | null | [
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# RogerMerge-12B-MoE
RogerMerge-12B-MoE is a Mixture of Experts (MoE) made with the following models using LazyMergekit:
* allknowingroger/MultiverseEx26-7B-slerp
* allknowingroger/PercivalMelodias-7B-slerp
## Configuration
## Usage
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | skitzobaka/SFT_Finetuned_Gemma_2B | null | [
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# Model Card for Model ID
## Model Details
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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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text-generation | transformers |
# NeuralSynthesis-7b-v0.4-slerp
NeuralSynthesis-7b-v0.4-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [allknowingroger/MultiverseEx26-7B-slerp](https://huggingface.co/allknowingroger/MultiverseEx26-7B-slerp)
* [K... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "allknowingroger/MultiverseEx26-7B-slerp", "Kukedlc/NeuralSynthesis-7B-v0.1"], "base_model": ["allknowingroger/MultiverseEx26-7B-slerp", "Kukedlc/NeuralSynthesis-7B-v0.1"]} | Kukedlc/NeuralSynthesis-7b-v0.4-slerp | null | [
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# NeuralSynthesis-7b-v0.4-slerp
NeuralSynthesis-7b-v0.4-slerp is a merge of the following models using LazyMergekit:
* allknowingroger/MultiverseEx26-7B-slerp
* Kukedlc/NeuralSynthesis-7B-v0.1
## Configuration
## Usage
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summarization | 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. -->
# BioNLP-intro-disc-PLOS
This model was trained from scratch on an unknown dataset.
## Model description
More information needed... | {"tags": ["summarization", "generated_from_trainer"], "model-index": [{"name": "BioNLP-intro-disc-PLOS", "results": []}]} | dtorber/BioNLP-intro-disc-PLOS | null | [
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|
# BioNLP-intro-disc-PLOS
This model was trained from scratch on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hy... | [
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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. -->
# violence-audio-Recognition-666
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "violence-audio-Recognition-666", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"name"... | Hemg/violence-audio-Recognition-666 | null | [
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| violence-audio-Recognition-666
==============================
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1258
* Accuracy: 0.9646
Model description
-----------------
More information needed
Intended... | [
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text-generation | transformers | 16 layers
# Uploaded model
- **Developed by:** LeroyDyer
- **License:** apache-2.0
- **Finetuned from model :** LeroyDyer/Mixtral_AI_MiniTron
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/unsl... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "LeroyDyer/Mixtral_AI_MiniTron"} | LeroyDyer/Mixtral_AI_MiniTron_3.75b | null | [
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| 16 layers
# Uploaded model
- Developed by: LeroyDyer
- License: apache-2.0
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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"]} | Dhara3078/ppo-Huggy | null | [
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"deep-reinforcement-learning",
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|
# 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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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. -->
# biogpt-ner
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown datas... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/biogpt", "model-index": [{"name": "biogpt-ner", "results": []}]} | ttlanhhh/biogpt-ner | null | [
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| biogpt-ner
==========
This model is a fine-tuned version of microsoft/biogpt on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1892
* Overall Precision: 0.4664
* Overall Recall: 0.5553
* Overall F1: 0.5070
* Overall Accuracy: 0.9572
Model description
-----------------
Mor... | [
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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": []} | riyadule/toxic_stack_gemma | null | [
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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
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text-to-image | diffusers |
# LoRA DreamBooth - squaadinc/1712941448370x493394559352216000
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
```
A photo of TOK
```
Use this keyword to trigger your custom model in your prompts.... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["jamine23/jamine23juliavzs"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "A photo of TOK", "inference": false} | squaadinc/1712941448370x493394559352216000 | null | [
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|
# LoRA DreamBooth - squaadinc/1712941448370x493394559352216000
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
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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": []} | abhayesian/BobzillaV11 | null | [
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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-bass-classifier5
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/dist... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["TheDuyx/augmented_bass_sounds"], "metrics": ["accuracy"], "base_model": "ntu-spml/distilhubert", "model-index": [{"name": "distilhubert-bass-classifier5", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "d... | TheDuyx/distilhubert-bass-classifier5 | null | [
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| distilhubert-bass-classifier5
=============================
This model is a fine-tuned version of ntu-spml/distilhubert on the bass\_design\_encoded dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0292
* Accuracy: 0.9982
Model description
-----------------
More information needed
I... | [
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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", "metrics": ["bleu"]} | Reyansh4/NMT_T5_wmt14_en_to_de | null | [
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text-generation | transformers |
# Model Card for Model ID
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null | transformers |
# Model Card for Model ID
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text-generation | transformers | Model Card for Fantastica-7b-Instruct-0.2-Italian
# 🇮🇹 Fantastica-7b-Instruct-0.2-Italian 🇮🇹
Fantastica-7b-Instruct-0.2-Italian is an Italian speaking, instruction finetuned, Large Language model. 🇮🇹
# COLAB NOTEBOOK (load in 4bit):
https://colab.research.google.com/drive/1txMLI6-rvo2lBmBazsP3-5WgYxVWiKzt?us... | {"language": ["it"], "license": "apache-2.0", "tags": ["Italian", "Mistral", "finetuning", "Text Generation"], "datasets": ["scribis/Wikipedia_it_Trame_Romanzi", "scribis/Corpus-Frasi-da-Opere-Letterarie", "scribis/Wikipedia-it-Trame-di-Film", "scribis/Wikipedia-it-Descrizioni-di-Dipinti", "scribis/Wikipedia-it-Mitolog... | scribis/Fantastica-7b-Instruct-0.2-Italian_merged | null | [
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# 🇮🇹 Fantastica-7b-Instruct-0.2-Italian 🇮🇹
Fantastica-7b-Instruct-0.2-Italian is an Italian speaking, instruction finetuned, Large Language model. 🇮🇹
# COLAB NOTEBOOK (load in 4bit):
URL
# Fantastica-7b-Instruct-0.2-Italian's peculiar features:
- Mistral-7B... | [
"# 🇮🇹 Fantastica-7b-Instruct-0.2-Italian 🇮🇹 \n\nFantastica-7b-Instruct-0.2-Italian is an Italian speaking, instruction finetuned, Large Language model. 🇮🇹",
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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": []} | aekang12/zephyr-7b-beta-Agent-Instruct | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | trl |
# Weni/WeniGPT-Agents-Mixtral-1.0.5-SFT
This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1] on the dataset Weni/wenigpt-agent-1.4.0 with the SFT trainer. It is part of the WeniGPT project for [Weni](https://weni.ai/).
Description: Experiment with SFT and a new tokenizer configuration for chat... | {"language": ["pt"], "license": "mit", "library_name": "trl", "tags": ["SFT", "WeniGPT"], "base_model": "mistralai/Mixtral-8x7B-Instruct-v0.1", "model-index": [{"name": "Weni/WeniGPT-Agents-Mixtral-1.0.5-SFT", "results": []}]} | Weni/WeniGPT-Agents-Mixtral-1.0.5-SFT | null | [
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# Weni/WeniGPT-Agents-Mixtral-1.0.5-SFT
This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1] on the dataset Weni/wenigpt-agent-1.4.0 with the SFT trainer. It is part of the WeniGPT project for Weni.
Description: Experiment with SFT and a new tokenizer configuration for chat template of mixtral... | [
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object-detection | 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. -->
Pollen Grain Object Detection model using DETR Resnet50 backbone
- **Developed by:** [More Information Needed]
- **Funded by [opti... | {"library_name": "transformers", "tags": []} | Charliesgt/pollen_detr_resnet50_benchmark | null | [
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#transformers #safetensors #detr #object-detection #arxiv-1910.09700 #endpoints_compatible #region-us
| Model Card for Model ID
=======================
Model Details
-------------
### Model Description
Pollen Grain Object Detection model using DETR Resnet50 backbone
* Developed by:
* Funded by [optional]:
* Shared by [optional]:
* Model type:
* Language(s) (NLP):
* License:
* Finetuned from model [optional]:
##... | [
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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. -->
# dbert-pii-detection-model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/dist... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "dbert-pii-detection-model", "results": []}]} | omshikhare/dbert-pii-detection-model | null | [
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| dbert-pii-detection-model
=========================
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1572
* Precision: 0.7413
* Recall: 0.8012
* F1: 0.7701
* Accuracy: 0.9433
* Classification Report: {'B-... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 6\n* mixed\\_prec... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - shljessie/tactile_img2img_LoRA
This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "dreambooth", "diffusers-training", "if", "if-diffusers"], "inference": true, "base_model": "runwayml/stable-diffusion-v1-5",... | shljessie/tactile_img2img_LoRA | null | [
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"base_model:runwayml/stable-diffusion-v1-5",
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"diffusers:StableDif... | null | 2024-04-12T17:13:50+00:00 | [] | [] | TAGS
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|
# DreamBooth - shljessie/tactile_img2img_LoRA
This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a tactile graphic using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
## Intended uses & limit... | [
"# DreamBooth - shljessie/tactile_img2img_LoRA\n\nThis is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a tactile graphic using DreamBooth.\nYou can find some example images in the following. \n\n\n\nDreamBooth for the text encoder was enabled: False.",
"## Intended u... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-uz-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_13_0"], "base_model": "facebook/wav2vec2-xls-r-300m", "model-index": [{"name": "wav2vec2-large-xls-r-300m-uz-colab", "results": []}]} | zohirjonsharipov/uz_asr_model | null | [
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"license:apache-2.0",
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|
# wav2vec2-large-xls-r-300m-uz-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3824
- eval_wer: 0.4664
- eval_runtime: 936.4524
- eval_samples_per_second: 13.157
- eval_steps_per_second... | [
"# wav2vec2-large-xls-r-300m-uz-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 0.3824\n- eval_wer: 0.4664\n- eval_runtime: 936.4524\n- eval_samples_per_second: 13.157\n- eval_steps_... | [
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text-generation | transformers | # Wukong-0.1-Mistral-7B-v0.2
Join Our Discord! https://discord.gg/cognitivecomputations
Wukong-0.1-Mistral-7B-v0.2 is a dealigned chat finetune of the original fantastic Mistral-7B-v0.2 model by ... | {"license": "apache-2.0", "datasets": ["teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "m-a-p/Code-Feedback"], "pipeline_tag": "text-generation"} | RESMPDEV/Wukong-0.1-Mistral-7B-v0.2 | null | [
"transformers",
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"text-generation",
"dataset:teknium/OpenHermes-2.5",
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"dataset:m-a-p/Code-Feedback",
"license:apache-2.0",
"autotrain_compatible",
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"regi... | null | 2024-04-12T17:15:47+00:00 | [] | [] | TAGS
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| # Wukong-0.1-Mistral-7B-v0.2
Join Our Discord! URL
!image/jpeg
Wukong-0.1-Mistral-7B-v0.2 is a dealigned chat finetune of the original fantastic Mistral-7B-v0.2 model by the Mistral team.
This model was trained on the teknium OpenHeremes-2.5 dataset, code datasets from Multimodal Art Projection URL, and the Dolphi... | [
"# Wukong-0.1-Mistral-7B-v0.2\n\nJoin Our Discord! URL \n\n!image/jpeg\n\nWukong-0.1-Mistral-7B-v0.2 is a dealigned chat finetune of the original fantastic Mistral-7B-v0.2 model by the Mistral team.\n\nThis model was trained on the teknium OpenHeremes-2.5 dataset, code datasets from Multimodal Art Projection URL, a... | [
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text-to-image | diffusers |
# AutoTrain SDXL LoRA DreamBooth - Suiren00/dreambooth_stablediffusion_test_kz
<Gallery />
## Model description
These are Suiren00/dreambooth_stablediffusion_test_kz LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using [DreamBooth](https://dreambooth.github.io/).
... | {"license": "openrail++", "tags": ["autotrain", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora", "template:sd-lora"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "a photo of CHAN wearing clothes"} | Suiren00/dreambooth_stablediffusion_test_kz | null | [
"diffusers",
"autotrain",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"text-to-image",
"lora",
"template:sd-lora",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
] | null | 2024-04-12T17:17:04+00:00 | [] | [] | TAGS
#diffusers #autotrain #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# AutoTrain SDXL LoRA DreamBooth - Suiren00/dreambooth_stablediffusion_test_kz
<Gallery />
## Model description
These are Suiren00/dreambooth_stablediffusion_test_kz LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was en... | [
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"## Model description\n\nThese are Suiren00/dreambooth_stablediffusion_test_kz LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.\n\nThe weights were trained using DreamBooth.\n\nLoRA for the text en... | [
"TAGS\n#diffusers #autotrain #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us \n",
"# AutoTrain SDXL LoRA DreamBooth - Suiren00/dreambooth_stablediffusion_test_kz\n\n<Gallery />",
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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. -->
# nuovo_amazon_kindle_sentiment_analysis
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-bas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-uncased", "model-index": [{"name": "nuovo_amazon_kindle_sentiment_analysis", "results": []}]} | denise227/nuovo_amazon_kindle_sentiment_analysis | null | [
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"base_model:bert-base-uncased",
"license:apache-2.0",
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"endpoints_compatible",
"region:us"
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#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# nuovo_amazon_kindle_sentiment_analysis
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Traini... | [
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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. -->
# fine-tuning-dolphin-mistral-with-webglm-qa-with-lora_1
This model is a fine-tuned version of [cognitivecomputations/dolphin-2.8-... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "cognitivecomputations/dolphin-2.8-mistral-7b-v02", "model-index": [{"name": "fine-tuning-dolphin-mistral-with-webglm-qa-with-lora_1", "results": []}]} | Gunslinger3D/fine-tuning-dolphin-mistral-with-webglm-qa-with-lora_1 | null | [
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#peft #safetensors #generated_from_trainer #base_model-cognitivecomputations/dolphin-2.8-mistral-7b-v02 #license-apache-2.0 #region-us
| fine-tuning-dolphin-mistral-with-webglm-qa-with-lora\_1
=======================================================
This model is a fine-tuned version of cognitivecomputations/dolphin-2.8-mistral-7b-v02 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2999
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. -->
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": []} | artixjain/diff_instr_model_2 | null | [
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"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
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text-generation | transformers | # Misted v2 7B
This is another version of [misted-7b](https://huggingface.co/walmart-the-bag/misted-7b). This creation was designed to tackle coding, provide instructions, solve riddles, and fulfill a variety of purposes. It was developed using the slerp approach, which involved combining several mistral models with mi... | {"language": ["en", "es"], "license": "apache-2.0", "library_name": "transformers", "tags": ["code", "mistral", "merge", "slerp"]} | Walmart-the-bag/Misted-v2-7B | null | [
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"safetensors",
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"text-generation",
"code",
"merge",
"slerp",
"conversational",
"en",
"es",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2024-04-12T17:21:29+00:00 | [] | [
"en",
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| # Misted v2 7B
This is another version of misted-7b. This creation was designed to tackle coding, provide instructions, solve riddles, and fulfill a variety of purposes. It was developed using the slerp approach, which involved combining several mistral models with misted-7b.
##### Quantizations
- gguf or imatrix
- hq... | [
"# Misted v2 7B\nThis is another version of misted-7b. This creation was designed to tackle coding, provide instructions, solve riddles, and fulfill a variety of purposes. It was developed using the slerp approach, which involved combining several mistral models with misted-7b.",
"##### Quantizations\n- gguf or i... | [
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null | mlx |
# GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.2`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.2) for more details on the model.
## Use wit... | {"tags": ["mlx"]} | GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.2-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"region:us"
] | null | 2024-04-12T17:26:01+00:00 | [] | [] | TAGS
#mlx #safetensors #qwen2 #region-us
|
# GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.2']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
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] |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Ppoyaa/Lumina-3
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week o... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["moe", "frankenmoe", "merge", "mergekit", "lazymergekit"], "base_model": "Ppoyaa/Lumina-3", "quantized_by": "mradermacher"} | mradermacher/Lumina-3-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-ner
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the foll... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-ner", "results": []}]} | shubhanmathur/bert-finetuned-ner | null | [
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"region:us"
] | null | 2024-04-12T17:28:04+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #gpt2 #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| bert-finetuned-ner
==================
This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1538
* Precision: 0.0968
* Recall: 0.0968
* F1: 0.0968
* Accuracy: 0.9655
Model description
-----------------
More information needed
Int... | [
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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. -->
# MLMA_Lab_8
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown datas... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "microsoft/biogpt", "model-index": [{"name": "MLMA_Lab_8", "results": []}]} | rupav02gmail/MLMA_Lab_8 | null | [
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"safetensors",
"gpt2",
"token-classification",
"generated_from_trainer",
"base_model:microsoft/biogpt",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-12T17:28:07+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #gpt2 #token-classification #generated_from_trainer #base_model-microsoft/biogpt #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| MLMA\_Lab\_8
============
This model is a fine-tuned version of microsoft/biogpt on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1458
* Precision: 0.4383
* Recall: 0.5324
* F1: 0.4808
* Accuracy: 0.9569
Model description
-----------------
More information needed
Inten... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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null | adapter-transformers |
# Adapter `BigTMiami/A2_adapter_seq_bn_classification_C_5` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head for classification.
... | {"tags": ["roberta", "adapter-transformers"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/A2_adapter_seq_bn_classification_C_5 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_helpfulness",
"region:us"
] | null | 2024-04-12T17:28:45+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/A2_adapter_seq_bn_classification_C_5' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usage
First, install '... | [
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null | transformers |
# Uploaded model
- **Developed by:** cackerman
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-7b-it-bnb-4bit
This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unslot... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "gemma", "trl"], "base_model": "unsloth/gemma-7b-it-bnb-4bit"} | cackerman/rewrites_gem7unsloth_4bit_ft_full | null | [
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"license:apache-2.0",
"endpoints_compatible",
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|
# Uploaded model
- Developed by: cackerman
- License: apache-2.0
- Finetuned from model : unsloth/gemma-7b-it-bnb-4bit
This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-generation | transformers |
# Model Card for Colossus 120b
Colussus 120b is a finetuning of alpindale/goliath-120b.
## 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... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers"} | ibivibiv/colossus_120b | null | [
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|
# Model Card for Colossus 120b
Colussus 120b is a finetuning of alpindale/goliath-120b.
!img
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- ... | [
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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": []} | ashnaz/suggest_doctors_symptoms | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
<!-- 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": "llama2", "tags": ["generated_from_trainer"], "base_model": "epfl-llm/meditron-7b", "model-index": [{"name": "models/packed", "results": []}]} | humantrue/packed-7b | null | [
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| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
models/packed
=============
This model is a fine-tuned version of epfl-llm/meditron-7b on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7796
Model description... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: cosine\n* lr\\_scheduler\\_warmup\\_steps: ... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
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... | {"library_name": "ml-agents", "tags": ["SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget"]} | pdejong/ppo-SnowballTarget | null | [
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#ml-agents #tensorboard #onnx #SnowballTarget #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SnowballTarget #region-us
|
# ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget
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 tuto... | [
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text-to-image | diffusers | # skin-hands-eyes-xl
<Gallery />
## Model description
This is a combined LoRA for both woman and men: for skin, hands, and eyes. It's not perfect; especially hands can look good right away or require some post-processing...by PolyhedronAI
## Trigger words
You should use `perfect eyes` to trigger the image gen... | {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "RAW photo, full body shot of a man: 30 year old warrior, wearing shiny metal armor, full sharp, detailed face, blue eyes, (high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, film grain, Fujifil... | MarkBW/skin-hands-eyes-xl | null | [
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"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
] | null | 2024-04-12T17:36:27+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
| # skin-hands-eyes-xl
<Gallery />
## Model description
This is a combined LoRA for both woman and men: for skin, hands, and eyes. It's not perfect; especially hands can look good right away or require some post-processing...by PolyhedronAI
## Trigger words
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null | 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. -->
# TrOCR-SIN-DeiT-Handwritten
This model is a fine-tuned version of [kavg/TrOCR-SIN-DeiT](https://huggingface.co/kavg/TrOCR-SIN-Dei... | {"tags": ["generated_from_trainer"], "base_model": "kavg/TrOCR-SIN-DeiT", "model-index": [{"name": "TrOCR-SIN-DeiT-Handwritten", "results": []}]} | kavg/TrOCR-SIN-DeiT-Handwritten | null | [
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| TrOCR-SIN-DeiT-Handwritten
==========================
This model is a fine-tuned version of kavg/TrOCR-SIN-DeiT on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.9839
* Cer: 0.5253
Model description
-----------------
More information needed
Intended uses & limitations
-... | [
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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": []} | aekang12/zephyr_ogft | null | [
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# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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": []} | Trubnik1967/zephyr-7b-beta-Agent-Instruct_v2 | null | [
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# Model Card for Model ID
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### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | i-pj/dqn-SpaceInvadersNoFrameskip-v4 | null | [
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"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
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#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
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null | 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. -->
# ckpts
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on a... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "facebook/hubert-base-ls960", "model-index": [{"name": "ckpts", "results": []}]} | Gizachew/ckpts | null | [
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| ckpts
=====
This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2980
* Accuracy: 0.9545
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
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. -->
# confused-gemma
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator ... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "google/gemma-2b", "model-index": [{"name": "confused-gemma", "results": []}]} | utkarshsingh99/confused-gemma | null | [
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#peft #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-google/gemma-2b #license-gemma #region-us
| confused-gemma
==============
This model is a fine-tuned version of google/gemma-2b on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 2.1404
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More infor... | [
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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. -->
# GemmaSheep-2B-LORA-TUNED
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the ... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer", "ipex", "GPU Max 1100"], "datasets": ["generator"], "base_model": "google/gemma-2b", "model-index": [{"name": "GemmaSheep-2B-LORA-TUNED", "results": []}]} | eduardo-alvarez/GemmaSheep-2B-LORA-TUNED | null | [
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"GPU Max 1100",
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#peft #safetensors #trl #sft #generated_from_trainer #ipex #GPU Max 1100 #dataset-generator #base_model-google/gemma-2b #license-gemma #region-us
| GemmaSheep-2B-LORA-TUNED
========================
This model is a fine-tuned version of google/gemma-2b on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 2.1445
Model description
-----------------
More information needed
Intended uses & limitations
--------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e... | [
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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. -->
# dallema
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer", "ipex", "GPU MAX 1100"], "datasets": ["generator"], "base_model": "google/gemma-2b", "model-index": [{"name": "dallema", "results": []}]} | ThejasElandassery/dallema | null | [
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#peft #safetensors #trl #sft #generated_from_trainer #ipex #GPU MAX 1100 #dataset-generator #base_model-google/gemma-2b #license-gemma #region-us
| dallema
=======
This model is a fine-tuned version of google/gemma-2b on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3748
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low... | {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.5 | null | [
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"safetensors",
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"autotrain_compatible",
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"region:us"
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#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GreenBit LLMs
=============
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using... | [
"### Zero-shot Evaluation\n\n\nWe evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using the 'llm\\_eval' library and list the results below:"
] | [
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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. -->
# Gemma2B-LORAfied
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generato... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer", "ipex", "GPU Max 1100"], "datasets": ["generator"], "base_model": "google/gemma-2b", "model-index": [{"name": "Gemma2B-LORAfied", "results": []}]} | migaraa/Gemma2B-LORAfied | null | [
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#peft #safetensors #trl #sft #generated_from_trainer #ipex #GPU Max 1100 #dataset-generator #base_model-google/gemma-2b #license-gemma #region-us
| Gemma2B-LORAfied
================
This model is a fine-tuned version of google/gemma-2b on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0206
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More i... | [
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null | adapter-transformers |
# Adapter `jgrc3/houlsby_adapter_classification_noPre` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head for classification.
Thi... | {"tags": ["adapter-transformers", "roberta"], "datasets": ["BigTMiami/amazon_helpfulness"]} | jgrc3/houlsby_adapter_classification_noPre | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_helpfulness",
"region:us"
] | null | 2024-04-12T17:44:12+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'jgrc3/houlsby_adapter_classification_noPre' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Usage
First, install 'adap... | [
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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. -->
# MLMA_Lab_8_GPT_model
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unk... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "microsoft/biogpt", "model-index": [{"name": "MLMA_Lab_8_GPT_model", "results": []}]} | rupav02gmail/MLMA_Lab_8_GPT_model | null | [
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"license:mit",
"autotrain_compatible",
"endpoints_compatible",
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"region:us"
] | null | 2024-04-12T17:47:38+00:00 | [] | [] | TAGS
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| MLMA\_Lab\_8\_GPT\_model
========================
This model is a fine-tuned version of microsoft/biogpt on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1507
* Precision: 0.4388
* Recall: 0.5464
* F1: 0.4867
* Accuracy: 0.9562
Model description
-----------------
More in... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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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. -->
# cdp-paf-classifier-limited
This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABer... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "alex-miller/ODABert", "model-index": [{"name": "cdp-paf-classifier-limited", "results": []}]} | alex-miller/cdp-paf-classifier-limited | null | [
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"text-classification",
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"base_model:alex-miller/ODABert",
"license:apache-2.0",
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"endpoints_compatible",
"region:us"
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#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-alex-miller/ODABert #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| cdp-paf-classifier-limited
==========================
This model is a fine-tuned version of alex-miller/ODABert on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1412
* Accuracy: 0.9561
* F1: 0.9534
* Precision: 0.9779
* Recall: 0.9301
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 60",
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null | transformers |
# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q5_K_S-GGUF
This model was converted to GGUF format from [`LeroyDyer/Mixtral_AI_CyberTron_Coder`](https://huggingface.co/LeroyDyer/Mixtral_AI_CyberTron_Coder) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "llama-cpp", "gguf-my-repo"], "base_model": "Mixtral_AI_CyberTron"} | LeroyDyer/Mixtral_AI_CyberTron_Coder-Q5_K_S-GGUF | null | [
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|
# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q5_K_S-GGUF
This model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_CyberTron_Coder' 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 CL... | [
"# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q5_K_S-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_CyberTron_Coder' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# output_model
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/TheBloke/Mist... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "model-index": [{"name": "output_model", "results": []}]} | aparnaanand/output_model | null | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ",
"license:apache-2.0",
"region:us"
] | null | 2024-04-12T17:47:45+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #base_model-TheBloke/Mistral-7B-Instruct-v0.1-GPTQ #license-apache-2.0 #region-us
|
# output_model
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hype... | [
"# output_model\n\nThis model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.",
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"# output_model\n\nThis model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.",
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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-v0.1"} | mille055/duke_chatbot0412_adapter2 | null | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:mistralai/Mistral-7B-v0.1",
"region:us"
] | null | 2024-04-12T17:48:42+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #safetensors #arxiv-1910.09700 #base_model-mistralai/Mistral-7B-v0.1 #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
#... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gemma-2b-dolly-tuned
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the gene... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer", "ipex", "GPU Max 1100"], "datasets": ["generator"], "base_model": "google/gemma-2b", "model-index": [{"name": "gemma-2b-dolly-tuned", "results": []}]} | Vinhduyle/gemma-2b-dolly-tuned | null | [
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"generated_from_trainer",
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"GPU Max 1100",
"dataset:generator",
"base_model:google/gemma-2b",
"license:gemma",
"region:us"
] | null | 2024-04-12T17:51:04+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #ipex #GPU Max 1100 #dataset-generator #base_model-google/gemma-2b #license-gemma #region-us
| gemma-2b-dolly-tuned
====================
This model is a fine-tuned version of google/gemma-2b on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0192
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low... | {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0 | null | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-12T17:51:11+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GreenBit LLMs
=============
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
### Zero-shot Evaluation
We evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using... | [
"### Zero-shot Evaluation\n\n\nWe evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using the 'llm\\_eval' library and list the results below:"
] | [
"TAGS\n#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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"TAGS\n#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n### Zero-shot Evaluation\n\n\nWe evaluate the zero-shot ability of low-bit quantized Qwen1.5 models using the 'llm\\_eval' library and lis... |
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. -->
# GemmaDoll-2b-dolly-LORA-Tune
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on ... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer", "ipex", "GPU Max 1100"], "datasets": ["generator"], "base_model": "google/gemma-2b", "model-index": [{"name": "GemmaDoll-2b-dolly-LORA-Tune", "results": []}]} | swathijn/GemmaDoll-2b-dolly-LORA-Tune | null | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"ipex",
"GPU Max 1100",
"dataset:generator",
"base_model:google/gemma-2b",
"license:gemma",
"region:us"
] | null | 2024-04-12T17:51:15+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #ipex #GPU Max 1100 #dataset-generator #base_model-google/gemma-2b #license-gemma #region-us
| GemmaDoll-2b-dolly-LORA-Tune
============================
This model is a fine-tuned version of google/gemma-2b on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 2.1517
Model description
-----------------
More information needed
Intended uses & limitations
------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e... | [
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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. -->
# GemmaSheep-2B-LORA-TUNED
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the ... | {"license": "gemma", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "google/gemma-2b", "model-index": [{"name": "GemmaSheep-2B-LORA-TUNED", "results": []}]} | quasar1256/gemmalearnnew | null | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:google/gemma-2b",
"license:gemma",
"region:us"
] | null | 2024-04-12T17:51:40+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-google/gemma-2b #license-gemma #region-us
| GemmaSheep-2B-LORA-TUNED
========================
This model is a fine-tuned version of google/gemma-2b on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 2.1504
Model description
-----------------
More information needed
Intended uses & limitations
--------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e... | [
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null | mlx |
# GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.5`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.5) for more details on the model.
## Use wit... | {"tags": ["mlx"]} | GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.5-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"region:us"
] | null | 2024-04-12T17:52:05+00:00 | [] | [] | TAGS
#mlx #safetensors #qwen2 #region-us
|
# GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.5-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-2.5']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
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] |
null | transformers |
# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q4_K_S-GGUF
This model was converted to GGUF format from [`LeroyDyer/Mixtral_AI_CyberTron_Coder`](https://huggingface.co/LeroyDyer/Mixtral_AI_CyberTron_Coder) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "llama-cpp", "gguf-my-repo"], "base_model": "Mixtral_AI_CyberTron"} | LeroyDyer/Mixtral_AI_CyberTron_Coder-Q4_K_S-GGUF | null | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:Mixtral_AI_CyberTron",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-12T17:54:35+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #text-generation-inference #unsloth #mistral #trl #llama-cpp #gguf-my-repo #en #base_model-Mixtral_AI_CyberTron #license-apache-2.0 #endpoints_compatible #region-us
|
# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q4_K_S-GGUF
This model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_CyberTron_Coder' 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 CL... | [
"# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q4_K_S-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_CyberTron_Coder' 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 ... | [
"TAGS\n#transformers #gguf #text-generation-inference #unsloth #mistral #trl #llama-cpp #gguf-my-repo #en #base_model-Mixtral_AI_CyberTron #license-apache-2.0 #endpoints_compatible #region-us \n",
"# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q4_K_S-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_... | [
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"TAGS\n#transformers #gguf #text-generation-inference #unsloth #mistral #trl #llama-cpp #gguf-my-repo #en #base_model-Mixtral_AI_CyberTron #license-apache-2.0 #endpoints_compatible #region-us \n# LeroyDyer/Mixtral_AI_CyberTron_Coder-Q4_K_S-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_Cyb... |
null | mlx |
# GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0) for more details on the model.
## Use wit... | {"tags": ["mlx"]} | GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0-mlx | null | [
"mlx",
"safetensors",
"qwen2",
"region:us"
] | null | 2024-04-12T17:56:26+00:00 | [] | [] | TAGS
#mlx #safetensors #qwen2 #region-us
|
# GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0']().
Refer to the original model card for more details on the model.
## Use with mlx
| [
"# GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0-mlx\nThis quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-0.5B-Chat-layer-mix-bpw-3.0']().\nRefer to the original model card for more details on the model.",
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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... | {"tags": ["generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-hf", "model-index": [{"name": "med-lora/Llama2-Medtext-txt-lora-epochs-2-lr-0001", "results": []}]} | ethensanchez/Llama2-Medtext-txt-lora-epochs-2-lr-0001 | null | [
"transformers",
"pytorch",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-hf",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-12T17:56:47+00:00 | [] | [] | TAGS
#transformers #pytorch #llama #text-generation #generated_from_trainer #base_model-meta-llama/Llama-2-7b-hf #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| <img src="URL alt="Built with Axolotl" width="200" height="32"/>
See axolotl config
axolotl version: '0.4.0'
med-lora/Llama2-Medtext-txt-lora-epochs-2-lr-0001
=================================================
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset.
It achieves the f... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 8\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 64\n... | [
"TAGS\n#transformers #pytorch #llama #text-generation #generated_from_trainer #base_model-meta-llama/Llama-2-7b-hf #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_ra... | [
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null | transformers |
# LeroyDyer/Mixtral_AI_MiniTron_II-Q4_K_S-GGUF
This model was converted to GGUF format from [`LeroyDyer/Mixtral_AI_MiniTron_II`](https://huggingface.co/LeroyDyer/Mixtral_AI_MiniTron_II) 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": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "llama-cpp", "gguf-my-repo"], "base_model": "LeroyDyer/Mixtral_AI_MiniTron"} | LeroyDyer/Mixtral_AI_MiniTron_II-Q4_K_S-GGUF | null | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:LeroyDyer/Mixtral_AI_MiniTron",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-12T17:57:20+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #text-generation-inference #unsloth #mistral #trl #llama-cpp #gguf-my-repo #en #base_model-LeroyDyer/Mixtral_AI_MiniTron #license-apache-2.0 #endpoints_compatible #region-us
|
# LeroyDyer/Mixtral_AI_MiniTron_II-Q4_K_S-GGUF
This model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_MiniTron_II' 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_MiniTron_II-Q4_K_S-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_MiniTron_II' 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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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
| {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.2 | null | [
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"safetensors",
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"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-12T17:59:11+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # GreenBit LLMs
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
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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": []} | artixjain/diff_instr_model_3 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-12T18:00:18+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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null | adapter-transformers |
# Adapter `BigTMiami/A3_adapter_seq_bn_classification_from_pretraining_P_5_C_5` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [BigTMiami/amazon_helpfulness](https://huggingface.co/datasets/BigTMiami/amazon_helpfulness/) dataset and includes a prediction head... | {"tags": ["adapter-transformers", "roberta"], "datasets": ["BigTMiami/amazon_helpfulness"]} | BigTMiami/A3_adapter_seq_bn_classification_from_pretraining_P_5_C_5 | null | [
"adapter-transformers",
"roberta",
"dataset:BigTMiami/amazon_helpfulness",
"region:us"
] | null | 2024-04-12T18:00:36+00:00 | [] | [] | TAGS
#adapter-transformers #roberta #dataset-BigTMiami/amazon_helpfulness #region-us
|
# Adapter 'BigTMiami/A3_adapter_seq_bn_classification_from_pretraining_P_5_C_5' for roberta-base
An adapter for the 'roberta-base' model that was trained on the BigTMiami/amazon_helpfulness dataset and includes a prediction head for classification.
This adapter was created for usage with the Adapters library.
## Us... | [
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
| {"license": "apache-2.0"} | GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.5 | null | [
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"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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#transformers #safetensors #qwen2 #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # GreenBit LLMs
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
| [
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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="Dhara3078/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional a... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_rewar... | Dhara3078/q-FrozenLake-v1-4x4-noSlippery | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
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#Taxi-v3 #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 | gguf |
Author of this model: Microsoft, 2024. License: MIT.
Link to the original card: https://huggingface.co/microsoft/rho-math-7b-interpreter-v0.1
Prompt template: ChatML (according to llama.cpp's `server`)? Mistral (according to `tokenizer_config.json`)? Alpaca (according to text-generation-webui)? All three seem to wor... | {"license": "mit", "library_name": "gguf", "tags": ["math"], "model_name": "rho-math-7b-interpreter-v0.1", "base_model": "microsoft/rho-math-7b-interpreter-v0.1", "model_creator": "Microsoft", "model_type": "mistral", "quantized_by": "arzeth"} | arzeth/rho-math-7b-interpreter-v0.1.imatrix-GGUF | null | [
"gguf",
"math",
"arxiv:2404.07965",
"base_model:microsoft/rho-math-7b-interpreter-v0.1",
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"2404.07965"
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#gguf #math #arxiv-2404.07965 #base_model-microsoft/rho-math-7b-interpreter-v0.1 #license-mit #region-us
|
Author of this model: Microsoft, 2024. License: MIT.
Link to the original card: URL
Prompt template: ChatML (according to URL's 'server')? Mistral (according to 'tokenizer_config.json')? Alpaca (according to text-generation-webui)? All three seem to work.
Context length: ?
According to their paper on arXiv, rho-ma... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="Dhara3078/taxi", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
en... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "taxi", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.54 +/- 2.7... | Dhara3078/taxi | null | [
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"custom-implementation",
"model-index",
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#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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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="Dhara3078/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": "taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.54 +/- ... | Dhara3078/taxi-v3 | null | [
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#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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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": []} | Grayx/unstable_2137 | null | [
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#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Shared by [optional]:
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | ed001/datascience-coder-6.7b-v0.2 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
<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 1B
<!-- 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"]} | allenai/OLMo-1B-hf | null | [
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] | TAGS
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| <img src="URL alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
Model Card for OLMo 1B
======================
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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null | null | ---
license: apache-2.0
---import requests
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
from datasets import Dataset
from transformers import GPT2Tokenizer, GPT2LMHeadModel, Trainer, TrainingArguments
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"region:us"
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#region-us
| ---
license: apache-2.0
---import requests
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
from datasets import Dataset
from transformers import GPT2Tokenizer, GPT2LMHeadModel, Trainer, TrainingArguments
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null | mlx |
# GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from [`GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.2`]().
Refer to the [original model card](https://huggingface.co/GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.2) for more details on the model.
## Use wit... | {"tags": ["mlx"]} | GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.2-mlx | null | [
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#mlx #safetensors #qwen2 #region-us
|
# GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.2-mlx
This quantized low-bit model was converted to MLX format from ['GreenBitAI/Qwen-1.5-1.8B-Chat-layer-mix-bpw-2.2']().
Refer to the original model card for more details on the model.
## Use with mlx
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summarization | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-smal... | {"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/mt5-small", "model-index": [{"name": "mt5-small-finetuned-amazon-en-es", "results": []}]} | JohnDoe70/mt5-small-finetuned-amazon-en-es | null | [
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| 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:
* Loss: 1.0471
* Rouge1: 35.9205
* Rouge2: 22.7367
* Rougel: 32.7559
* Rougelsum: 32.5835
Model description
-----... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5.6e-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: 8",
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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="samzapo/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional att... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | samzapo/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-12T18:20:58+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 | transformers |
# Uploaded model
- **Developed by:** cackerman
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-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/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "unsloth/mistral-7b-instruct-v0.2-bnb-4bit"} | cackerman/rewrites_mistral7unsloth_4bit_ft_full | null | [
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|
# Uploaded model
- Developed by: cackerman
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.2-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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null | transformers |
# 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": []} | artixjain/diff_instr_model_4 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Shared by [optional]:
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [WizardLM/WizardMath-7B-V1.1](https://huggin... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["WizardLM/WizardMath-7B-V1.1", "NousResearch/Hermes-2-Pro-Mistral-7B"]} | mergekit-community/mergekit-slerp-nfoezyj | null | [
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| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* WizardLM/WizardMath-7B-V1.1
* NousResearch/Hermes-2-Pro-Mistral-7B
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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": []} | skitzobaka/gemma_sft_model | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | null |
This model is a test using Intel Gaudi Habana 2 chips using DDP training. Trained over 8xGaudi-2 Chips using DDP and Deepspeed using the openassistant dataset.
# Prompt Format
This model uses ChatML as the prompt format.
```
<|im_start|>system
You are a helpful assistant for Python which outputs in Markdown forma... | {"license": "apache-2.0", "datasets": ["timdettmers/openassistant-guanaco"]} | ndavidson/Phi-2-openassistant | null | [
"safetensors",
"optimum_habana",
"dataset:timdettmers/openassistant-guanaco",
"license:apache-2.0",
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#safetensors #optimum_habana #dataset-timdettmers/openassistant-guanaco #license-apache-2.0 #region-us
|
This model is a test using Intel Gaudi Habana 2 chips using DDP training. Trained over 8xGaudi-2 Chips using DDP and Deepspeed using the openassistant dataset.
# Prompt Format
This model uses ChatML as the prompt format.
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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. -->
# t5-small-finetuned-xsum
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
I... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["xsum"], "base_model": "t5-small", "model-index": [{"name": "t5-small-finetuned-xsum", "results": []}]} | edithram23/t5-small-finetuned-xsum | null | [
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| t5-small-finetuned-xsum
=======================
This model is a fine-tuned version of t5-small on the xsum dataset.
It achieves the following results on the evaluation set:
* Loss: 3.5393
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="samzapo/Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
e... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- ... | samzapo/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-12T18:28:59+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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] |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-finetuned-squad
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert-base-cased", "model-index": [{"name": "distilbert-finetuned-squad", "results": []}]} | noushsuon/distilbert-finetuned-squad | null | [
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"endpoints_compatible",
"region:us"
] | null | 2024-04-12T18:31:23+00:00 | [] | [] | TAGS
#transformers #safetensors #distilbert #question-answering #generated_from_trainer #base_model-distilbert-base-cased #license-apache-2.0 #endpoints_compatible #region-us
|
# distilbert-finetuned-squad
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyper... | [
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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. -->
# cdp-aa-classifier-synth-limited
This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/O... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "alex-miller/ODABert", "model-index": [{"name": "cdp-aa-classifier-synth-limited", "results": []}]} | alex-miller/cdp-aa-classifier-synth-limited | null | [
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"autotrain_compatible",
"endpoints_compatible",
"region:us"
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| cdp-aa-classifier-synth-limited
===============================
This model is a fine-tuned version of alex-miller/ODABert on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2051
* Accuracy: 0.9071
* F1: 0.9065
* Precision: 0.9130
* Recall: 0.9
Model description
-------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-06\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 40",
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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. -->
# legal-bert-base-uncased
This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/l... | {"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall"], "base_model": "nlpaueb/legal-bert-base-uncased", "model-index": [{"name": "legal-bert-base-uncased", "results": []}]} | xshubhamx/legal-bert-base-uncased | null | [
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] | null | 2024-04-12T18:35:14+00:00 | [] | [] | TAGS
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| legal-bert-base-uncased
=======================
This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1536
* Accuracy: 0.8203
* Precision: 0.8212
* Recall: 0.8203
* Precision Macro: 0.7660
* Recall Macro: 0.754... | [
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text-generation | transformers |
<img src="https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1/resolve/main/logo.png" alt="Zephyr 141B Logo" width="400" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Model Card for Zephyr 141B-A35B
Zephyr is a series of language models that are trained to act as helpful assistants. ... | {"license": "apache-2.0", "tags": ["trl", "orpo", "generated_from_trainer"], "datasets": ["argilla/distilabel-capybara-dpo-7k-binarized"], "base_model": "mistral-community/Mixtral-8x22B-v0.1", "model-index": [{"name": "zephyr-orpo-141b-A35b-v0.1", "results": []}]} | blockblockblock/zephyr-orpo-141b-A35b-v0.1-bpw4 | null | [
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Model Card for Zephyr 141B-A35B
===============================
Zephyr is a series of language models that are trained to act as helpful assistants. Zephyr 141B-A35B is the latest model in the series, a... | [
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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. -->
# results
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown dataset.... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/biogpt", "model-index": [{"name": "results", "results": []}]} | SweetZiyi/results | null | [
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"region:us"
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|
# results
This model is a fine-tuned version of microsoft/biogpt on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_precision: 0.4837
- eval_recall: 0.5349
- eval_f1: 0.5080
- eval_accuracy: 0.9438
- eval_loss: 0.1802
- eval_runtime: 14.3435
- eval_samples_per_second: 65.605
- ev... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/saucam/Orpomis-Prime-7B
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up ... | {"language": ["en"], "library_name": "transformers", "tags": ["merge", "mergekit"], "base_model": "saucam/Orpomis-Prime-7B", "quantized_by": "mradermacher"} | mradermacher/Orpomis-Prime-7B-GGUF | null | [
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"en"
] | TAGS
#transformers #gguf #merge #mergekit #en #base_model-saucam/Orpomis-Prime-7B #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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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": []} | Juniplayground/juniper-mxbai-embed-large-v1-v10 | null | [
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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.
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- Funded by [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. -->
# Psoriasis-Project-M-beit-base-patch16-224-pt22k-ft22k
This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt2... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224-pt22k-ft22k", "model-index": [{"name": "Psoriasis-Project-M-beit-base-patch16-224-pt22k-ft22k", "results": []}]} | ahmedesmail16/Psoriasis-Project-M-beit-base-patch16-224-pt22k-ft22k | null | [
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| Psoriasis-Project-M-beit-base-patch16-224-pt22k-ft22k
=====================================================
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1695
* Accuracy: 0.9792
Model desc... | [
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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": []} | EdBerg/opt-125m-gptq-4bit | null | [
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|
# Model Card for Model ID
## Model Details
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text-generation | transformers |
# Orpomis-Prime-7B-dare
Orpomis-Prime-7B-dare is a merge of the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
* [kaist-ai/mistral-orpo-beta](https://huggingface.co/kaist-ai/mistral-orpo-beta)
* [NousResearch/Hermes... | {"tags": ["merge", "mergekit", "kaist-ai/mistral-orpo-beta", "NousResearch/Hermes-2-Pro-Mistral-7B"], "base_model": ["kaist-ai/mistral-orpo-beta", "NousResearch/Hermes-2-Pro-Mistral-7B"]} | saucam/Orpomis-Prime-7B-dare | null | [
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"autotrain_compatible",
"endpo... | null | 2024-04-12T18:44:22+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #kaist-ai/mistral-orpo-beta #NousResearch/Hermes-2-Pro-Mistral-7B #conversational #base_model-kaist-ai/mistral-orpo-beta #base_model-NousResearch/Hermes-2-Pro-Mistral-7B #autotrain_compatible #endpoints_compatible #text-generation-inference #reg... |
![](URL
# Orpomis-Prime-7B-dare
Orpomis-Prime-7B-dare is a merge of the following models using Mergekit:
* kaist-ai/mistral-orpo-beta
* NousResearch/Hermes-2-Pro-Mistral-7B
## Configuration
## Usage
## Sample Run
| [
"# Orpomis-Prime-7B-dare\n\nOrpomis-Prime-7B-dare is a merge of the following models using Mergekit:\n* kaist-ai/mistral-orpo-beta\n* NousResearch/Hermes-2-Pro-Mistral-7B",
"## Configuration",
"## Usage",
"## Sample Run"
] | [
"TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit #kaist-ai/mistral-orpo-beta #NousResearch/Hermes-2-Pro-Mistral-7B #conversational #base_model-kaist-ai/mistral-orpo-beta #base_model-NousResearch/Hermes-2-Pro-Mistral-7B #autotrain_compatible #endpoints_compatible #text-generation-inferenc... | [
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"TAGS\n#transformers #safetensors #mistral #text-generation #merge #mergekit #kaist-ai/mistral-orpo-beta #NousResearch/Hermes-2-Pro-Mistral-7B #conversational #base_model-kaist-ai/mistral-orpo-beta #base_model-NousResearch/Hermes-2-Pro-Mistral-7B #autotrain_compatible #endpoints_compatible #text-generation-inferenc... |
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. -->
# platzi-distilroberta-base-mrpc-glue-jdgalvan
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "distilroberta-base", "model-index": [{"name": "platzi-distilroberta-base-mrpc-glue-jdgalvan", "results": []}]} | platzi/platzi-distilroberta-base-mrpc-glue-jdgalvan | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:distilroberta-base",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-12T18:47:05+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-distilroberta-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| platzi-distilroberta-base-mrpc-glue-jdgalvan
============================================
This model is a fine-tuned version of distilroberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7015
* Accuracy: 0.8456
* F1: 0.8901
Model description
-----------------
Mo... | [
"### 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* num\\_epochs: 3",
"### Training... | [
"TAGS\n#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-distilroberta-base #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* lea... | [
56,
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"TAGS\n#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-distilroberta-base #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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