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text-generation | transformers |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_pat... | {"license": "other", "library_name": "transformers", "tags": ["autotrain", "text-generation-inference", "text-generation", "peft"], "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | KvrParaskevi/Hotel-Assistant-Attempt5-Llama-2-7b | null | [
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#transformers #safetensors #llama #text-generation #autotrain #text-generation-inference #peft #conversational #license-other #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
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text-generation | transformers | # [MaziyarPanahi/Experiment26Strangemerges_30-7B-GGUF](https://huggingface.co/MaziyarPanahi/Experiment26Strangemerges_30-7B-GGUF)
- Model creator: [automerger](https://huggingface.co/automerger)
- Original model: [automerger/Experiment26Strangemerges_30-7B](https://huggingface.co/automerger/Experiment26Strangemerges_30... | {"tags": ["quantized", "2-bit", "3-bit", "4-bit", "5-bit", "6-bit", "8-bit", "GGUF", "transformers", "safetensors", "mistral", "text-generation", "merge", "mergekit", "lazymergekit", "automerger", "base_model:Gille/StrangeMerges_30-7B-slerp", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "text-g... | MaziyarPanahi/Experiment26Strangemerges_30-7B-GGUF | null | [
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- Model creator: automerger
- Original model: automerger/Experiment26Strangemerges_30-7B
## Description
MaziyarPanahi/Experiment26Strangemerges_30-7B-GGUF contains GGUF format model files for automerger/Experiment26Strangemerges_30-7B.
## How to use
Thanks to TheBl... | [
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null | null | GGUFs for Faro Yi 34B 200K - https://huggingface.co/wenbopan/Faro-Yi-34B-200K
iMatrix GGUFs generated with Kalomaze's semi-random groups_merged.txt
Files >50gb have been split with peazip. Recombine with peazip, 7zip, or simple concatenate command. | {"language": ["zh", "en"], "license": "mit", "datasets": ["wenbopan/Fusang-v1", "wenbopan/OpenOrca-zh-20k"]} | MarsupialAI/Faro-Yi-34B-200K_iMatrix_GGUF | null | [
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| GGUFs for Faro Yi 34B 200K - URL
iMatrix GGUFs generated with Kalomaze's semi-random groups_merged.txt
Files >50gb have been split with peazip. Recombine with peazip, 7zip, or simple concatenate command. | [] | [
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text-to-image | diffusers |
# LoRA DreamBooth - squaadinc/1711991256141x361121682986177400
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:
```
in the style of TOK
```
Use this keyword to trigger your custom model in your pro... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["Frank535/KCS"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "in the style of TOK", "inference": false} | squaadinc/1711991256141x361121682986177400 | null | [
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"stable-diffusion-xl",
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"lora",
"dataset:Frank535/KCS",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
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|
# LoRA DreamBooth - squaadinc/1711991256141x361121682986177400
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:
Use this keyword to trigger your custom model in your prompts.
LoRA for the text en... | [
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swin-tiny-patch4-window7-224", "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-eurosat", "results": [{"task": {"type": "image-classification", "name": "Image Clas... | mohameddemes/swin-tiny-patch4-window7-224-finetuned-eurosat | null | [
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| swin-tiny-patch4-window7-224-finetuned-eurosat
==============================================
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0625
* Accuracy: 0.9765
Model description
------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 128\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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reinforcement-learning | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Docum... | {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | DiegoT200/SoccerTwos | null | [
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"tensorboard",
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"SoccerTwos",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SoccerTwos",
"region:us"
] | null | 2024-04-01T17:13:57+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #SoccerTwos #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us
|
# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A *short tutorial* ... | [
"# poca Agent playing SoccerTwos\n This is a trained model of a poca agent playing SoccerTwos\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short ... | [
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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. -->
# mDeBERTa-v3-base-mnli-xnli-finetune_v1
This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-mnli-xnli](https://h... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "MoritzLaurer/mDeBERTa-v3-base-mnli-xnli", "model-index": [{"name": "mDeBERTa-v3-base-mnli-xnli-finetune_v1", "results": []}]} | BishanSingh246/mDeBERTa-v3-base-mnli-xnli-finetune_v1 | null | [
"transformers",
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"license:mit",
"autotrain_compatible",
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"region:us"
] | null | 2024-04-01T17:16:23+00:00 | [] | [] | TAGS
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|
# mDeBERTa-v3-base-mnli-xnli-finetune_v1
This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-mnli-xnli on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training p... | [
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"## Intended uses & limitations\n\nMore information needed",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K14ac-seqsight_4096_512_15M-L8
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_4096_512_15M-L8", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_4096_512_15M-L8 | null | [
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] | null | 2024-04-01T17:17:53+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_4096\_512\_15M-L8
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6564
* F1 Score: 0.6104
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K14ac-seqsight_4096_512_15M-L1
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_4096_512_15M-L1", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_4096_512_15M-L1 | null | [
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"safetensors",
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"region:us"
] | null | 2024-04-01T17:17:53+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_4096\_512\_15M-L1
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6518
* F1 Score: 0.6149
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K14ac-seqsight_4096_512_15M-L32
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K14ac-seqsight_4096_512_15M-L32", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K14ac-seqsight_4096_512_15M-L32 | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_15M",
"region:us"
] | null | 2024-04-01T17:18:21+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K14ac-seqsight\_4096\_512\_15M-L32
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K14ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7299
* F1 Score: 0.606... | [
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text2text-generation | transformers |
# FRED-T5-large-instruct-v0.1
Model was trained by [bond005](https://scholar.google.ru/citations?user=3AJKH38AAAAJ) for automatically editing text and generating answers to various questions in Russian. The solved tasks are:
1. **asr_correction** This task is to correct errors, restore punctuation and capitalizatio... | {"language": "ru", "license": "apache-2.0", "tags": ["PyTorch", "Transformers"], "widget": [{"text": "<LM>\u0418\u0441\u043f\u0440\u0430\u0432\u044c, \u043f\u043e\u0436\u0430\u043b\u0443\u0439\u0441\u0442\u0430, \u043e\u0448\u0438\u0431\u043a\u0438 \u0440\u0430\u0441\u043f\u043e\u0437\u043d\u0430\u0432\u0430\u043d\u043... | bond005/FRED-T5-large-instruct-v0.1 | null | [
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| FRED-T5-large-instruct-v0.1
===========================
Model was trained by bond005 for automatically editing text and generating answers to various questions in Russian. The solved tasks are:
1. asr\_correction This task is to correct errors, restore punctuation and capitalization in the ASR output (in particular... | [
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null | null | # ItaIla
ItaIla is a pre-trained model specifically tailored for rapid voice model training in Italian.
With its unique feature set, ItaIla empowers users to train voice models with as little as two minutes of data and a minimal number of epochs,
typically around 150, while still achieving hi... | {} | TheStinger/itaila | null | [
"region:us"
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#region-us
| # ItaIla
!itaila
ItaIla is a pre-trained model specifically tailored for rapid voice model training in Italian.
With its unique feature set, ItaIla empowers users to train voice models with as little as two minutes of data and a minimal number of epochs,
typically around 150, while still achieving high-quality resul... | [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | sezinarseven/mbti-classification-2 | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# phi-1_5-finetuned-gsm8k
This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on t... | {"license": "mit", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-1_5", "model-index": [{"name": "phi-1_5-finetuned-gsm8k", "results": []}]} | yash-aswi-bhavah15/phi-1_5-finetuned-gsm8k | null | [
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|
# phi-1_5-finetuned-gsm8k
This model is a fine-tuned version of microsoft/phi-1_5 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 hyperparameter... | [
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text-to-image | diffusers | ### My-Pet-Cat Dreambooth model trained by nayanraut1412 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: A335
Sample pictures of this concept:
| {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | nayanraut1412/my-pet-cat | null | [
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| ### My-Pet-Cat Dreambooth model trained by nayanraut1412 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: A335
Sample pictures of this concept:
!0
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | sezinarseven/mbti-classification-3 | null | [
"transformers",
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"1910.09700"
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#transformers #safetensors #bert #text-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me2-seqsight_4096_512_15M-L1
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_4096_512_15M-L1", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_4096_512_15M-L1 | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_4096\_512\_15M-L1
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6424
* F1 Score: 0.6204
... | [
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text-to-image | diffusers | ### cars Dreambooth model trained by dfjdjtng following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX199932gAS
Sample pictures of this concept:
.jpg)
| {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | dfjdjtng/cars | null | [
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Project Submission Code: GoX199932gAS
Sample pictures of this concept:
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null | null | GGUFs for Pippafeet 11B 0.2 - https://huggingface.co/nonetrix/pippafeet-11B-0.2
iMatrix GGUFs generated with Kalomaze's semi-random groups_merged.txt | {} | MarsupialAI/pippafeet-11B-0.2_iMatrix_GGUF | null | [
"gguf",
"region:us"
] | null | 2024-04-01T17:28:04+00:00 | [] | [] | TAGS
#gguf #region-us
| GGUFs for Pippafeet 11B 0.2 - URL
iMatrix GGUFs generated with Kalomaze's semi-random groups_merged.txt | [] | [
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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]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "mistralai/Mistral-7B-Instruct-v0.2"} | sherrysi/Mistral7B_QLORA_cleaner_r8 | null | [
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|
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### Model Sources [optional]
- Repository:
- Paper [optional]:
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Frankhuhu/ppo-LunarLander-v2 | null | [
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"deep-reinforcement-learning",
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"region:us"
] | null | 2024-04-01T17:31:45+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
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. -->
# albert-xxlarge-v2-disaster-twitter-v2
This model is a fine-tuned version of [albert-xxlarge-v2](https://huggingface.co/albert-xx... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "albert-xxlarge-v2", "model-index": [{"name": "albert-xxlarge-v2-disaster-twitter-v2", "results": []}]} | JiaJiaCen/albert-xxlarge-v2-disaster-twitter-v2 | null | [
"transformers",
"tensorboard",
"safetensors",
"albert",
"text-classification",
"generated_from_trainer",
"base_model:albert-xxlarge-v2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-01T17:32:02+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #albert #text-classification #generated_from_trainer #base_model-albert-xxlarge-v2 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| albert-xxlarge-v2-disaster-twitter-v2
=====================================
This model is a fine-tuned version of albert-xxlarge-v2 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3921
* F1: 0.7893
Model description
-----------------
More information needed
Intended use... | [
"### 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: 3",
"### 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. -->
# finetunedPHP_starcoder2
This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-... | {"license": "bigcode-openrail-m", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "bigcode/starcoder2-3b", "model-index": [{"name": "finetunedPHP_starcoder2", "results": []}]} | Debasish365/finetunedPHP_starcoder2 | null | [
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"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:bigcode/starcoder2-3b",
"license:bigcode-openrail-m",
"region:us"
] | null | 2024-04-01T17:33:14+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #base_model-bigcode/starcoder2-3b #license-bigcode-openrail-m #region-us
|
# finetunedPHP_starcoder2
This model is a fine-tuned version of bigcode/starcoder2-3b 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 hyperpar... | [
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"## Training and evaluation data\n\nMore information needed",
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null | transformers | ## About
static quants of https://huggingface.co/mlabonne/Zebrafish-7B
<!-- provided-files -->
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 Discus... | {"language": ["en"], "license": "cc-by-nc-4.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit"], "base_model": "mlabonne/Zebrafish-7B", "quantized_by": "mradermacher"} | mradermacher/Zebrafish-7B-GGUF | null | [
"transformers",
"gguf",
"merge",
"mergekit",
"lazymergekit",
"en",
"base_model:mlabonne/Zebrafish-7B",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-01T17:34:10+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #merge #mergekit #lazymergekit #en #base_model-mlabonne/Zebrafish-7B #license-cc-by-nc-4.0 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
text-to-image | diffusers |
# LoRA DreamBooth - squaadinc/1711992893587x323030413431352640
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:
```
in the style of TOK
```
Use this keyword to trigger your custom model in your pro... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["RickGrimes001/iluminate2"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "in the style of TOK", "inference": false} | squaadinc/1711992893587x323030413431352640 | null | [
"diffusers",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"text-to-image",
"lora",
"dataset:RickGrimes001/iluminate2",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
] | null | 2024-04-01T17:35:22+00:00 | [] | [] | TAGS
#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-RickGrimes001/iluminate2 #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
|
# LoRA DreamBooth - squaadinc/1711992893587x323030413431352640
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:
Use this keyword to trigger your custom model in your prompts.
LoRA for the text en... | [
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text-generation | transformers |
# NeuralStock-7B-v3
NeuralStock-7B-v3 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
models:
- model: Kukedlc/NeuralMaths-Experiment-7b
- model: Kukedlc/NeuralArjuna-7B-DT
- model: Kuke... | {"tags": ["merge", "mergekit", "lazymergekit"]} | Kukedlc/NeuralStock-7B-v3 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-01T17:35:29+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# NeuralStock-7B-v3
NeuralStock-7B-v3 is a merge of the following models using LazyMergekit:
## Configuration
## Usage
| [
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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... | AbdulRaufSpg/dqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-01T17:37:48+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
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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": []} | RefalMachine/ruadapt_mistral7b_full_vo_1e4 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-01T17:38:58+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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. -->
# results
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown da... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/flan-t5-base", "model-index": [{"name": "results", "results": []}]} | adejumobi/results | null | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google/flan-t5-base",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-01T17:39:41+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-google/flan-t5-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| results
=======
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0272
* Rouge1: 0.0628
* Rouge2: 0.0003
* Rougel: 0.0616
* Rougelsum: 0.0627
Model description
-----------------
More information needed
Intended u... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 4\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-to-image | diffusers |
# AWPainting
## v1.2
### Description:
>
### Creator: DynamicWang
### Civitai Page: https://civitai.com/models/84476
You can use this with the [🧨Diffusers library](https://github.com/huggingface/diffusers)
### Diffusers
```py
from diffusers import ... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["Safetensors", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image"], "pipeline_tag": "text-to-image"} | sam749/AWPainting-v1-2 | null | [
"diffusers",
"safetensors",
"Safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | 2024-04-01T17:39:57+00:00 | [] | [] | TAGS
#diffusers #safetensors #Safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# AWPainting
## v1.2
!Generated Sample
### Description:
>
### Creator: DynamicWang
### Civitai Page: URL
You can use this with the Diffusers library
### Diffusers
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text-generation | null |
## Exllama v2 Quantizations of Faro-Yi-9B-200K
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.17">turboderp's ExLlamaV2 v0.0.17</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each branch contain... | {"language": ["zh", "en"], "license": "mit", "datasets": ["wenbopan/Fusang-v1", "wenbopan/OpenOrca-zh-20k"], "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/Faro-Yi-9B-200K-exl2 | null | [
"text-generation",
"zh",
"en",
"dataset:wenbopan/Fusang-v1",
"dataset:wenbopan/OpenOrca-zh-20k",
"license:mit",
"region:us"
] | null | 2024-04-01T17:41:20+00:00 | [] | [
"zh",
"en"
] | TAGS
#text-generation #zh #en #dataset-wenbopan/Fusang-v1 #dataset-wenbopan/OpenOrca-zh-20k #license-mit #region-us
| Exllama v2 Quantizations of Faro-Yi-9B-200K
-------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.17 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
Each branch contains an individual bits per weight, with the main... | [] | [
"TAGS\n#text-generation #zh #en #dataset-wenbopan/Fusang-v1 #dataset-wenbopan/OpenOrca-zh-20k #license-mit #region-us \n"
] | [
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] | [
"TAGS\n#text-generation #zh #en #dataset-wenbopan/Fusang-v1 #dataset-wenbopan/OpenOrca-zh-20k #license-mit #region-us \n"
] |
sentence-similarity | sentence-transformers |
# peulsilva/phrase-bert-setfit-500shots-ADE_CORPUS
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | peulsilva/phrase-bert-setfit-500shots-ADE_CORPUS | null | [
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] | null | 2024-04-01T17:41:35+00:00 | [] | [] | TAGS
#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# peulsilva/phrase-bert-setfit-500shots-ADE_CORPUS
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-trans... | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** Banach311
- **License:** apache-2.0
- **Finetuned from model :** Danielbrdz/Barcenas-Mistral-7b
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/un... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl"], "base_model": "Danielbrdz/Barcenas-Mistral-7b"} | Banach311/RBarcenas-Mistral-7b-AbstractiveQA2 | null | [
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|
# Uploaded model
- Developed by: Banach311
- License: apache-2.0
- Finetuned from model : Danielbrdz/Barcenas-Mistral-7b
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-generation | null |
## Llamacpp Quantizations of Faro-Yi-9B-200K
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2536">b2536</a> for quantization.
Original model: https://huggingface.co/wenbopan/Faro-Yi-9B-200K
Download a file (not the whole br... | {"language": ["zh", "en"], "license": "mit", "datasets": ["wenbopan/Fusang-v1", "wenbopan/OpenOrca-zh-20k"], "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/Faro-Yi-9B-200K-GGUF | null | [
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#gguf #text-generation #zh #en #dataset-wenbopan/Fusang-v1 #dataset-wenbopan/OpenOrca-zh-20k #license-mit #region-us
| Llamacpp Quantizations of Faro-Yi-9B-200K
-----------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
Download a file (not the whole branch) from below:
Want to support my work? Visit my ko-fi page here: URL
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-IDRiD
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](http... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-IDRiD", "results": []}]} | SJChaudhuri/swin-tiny-patch4-window7-224-finetuned-IDRiD | null | [
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#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| swin-tiny-patch4-window7-224-finetuned-IDRiD
============================================
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8534
* Accuracy: 0.7143
Model description
---------------... | [
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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. -->
# w2v2-base-pretrained_lr5e-5_at0.8_da0.4
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/fa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "w2v2-base-pretrained_lr5e-5_at0.8_da0.4", "results": []}]} | MelanieKoe/w2v2-base-pretrained_lr5e-5_at0.8_da0.4 | null | [
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#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-base #license-apache-2.0 #endpoints_compatible #region-us
| w2v2-base-pretrained\_lr5e-5\_at0.8\_da0.4
==========================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.6336
* Wer: 0.8377
Model description
-----------------
More information neede... | [
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null | null | This is a demo is a audio-only version of the approach described in the paper, ["EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling"](https://arxiv.org/abs/2401.00374)
```
@misc{liu2023emage,
title={EMAGE: Towards Unified Holistic Co-Speech Gesture Generatio... | {"license": "apache-2.0", "title": "EMAGE", "emoji": "\u26a1", "colorFrom": "yellow", "colorTo": "green", "sdk": "gradio", "sdk_version": "4.24.0", "app_file": "app.py", "pinned": false} | camenduru/EMAGE | null | [
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#arxiv-2401.00374 #license-apache-2.0 #region-us
| This is a demo is a audio-only version of the approach described in the paper, "EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling"
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text-generation | transformers |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_pat... | {"license": "other", "library_name": "transformers", "tags": ["autotrain", "text-generation-inference", "text-generation", "peft"], "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | shaswatamitra/westseverus-finetuned1 | null | [
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#transformers #safetensors #autotrain #text-generation-inference #text-generation #peft #conversational #license-other #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
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text-generation | transformers | # [MaziyarPanahi/Strangemerges_32Experiment28-7B-GGUF](https://huggingface.co/MaziyarPanahi/Strangemerges_32Experiment28-7B-GGUF)
- Model creator: [automerger](https://huggingface.co/automerger)
- Original model: [automerger/Strangemerges_32Experiment28-7B](https://huggingface.co/automerger/Strangemerges_32Experiment28... | {"tags": ["quantized", "2-bit", "3-bit", "4-bit", "5-bit", "6-bit", "8-bit", "GGUF", "transformers", "safetensors", "mistral", "text-generation", "merge", "mergekit", "lazymergekit", "automerger", "base_model:Gille/StrangeMerges_32-7B-slerp", "base_model:yam-peleg/Experiment28-7B", "license:apache-2.0", "autotrain_comp... | MaziyarPanahi/Strangemerges_32Experiment28-7B-GGUF | null | [
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- Model creator: automerger
- Original model: automerger/Strangemerges_32Experiment28-7B
## Description
MaziyarPanahi/Strangemerges_32Experiment28-7B-GGUF contains GGUF format model files for automerger/Strangemerges_32Experiment28-7B.
## How to use
Thanks to TheBl... | [
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text-to-image | diffusers |
# SDXL LoRA DreamBooth - linoyts/huggy_lora_v2_pivotal
<Gallery />
## Model description
### These are linoyts/huggy_lora_v2_pivotal LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
## Download model
### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- **LoRA**: download **[`h... | {"license": "openrail++", "tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "diffusers-training", "text-to-image", "diffusers", "lora", "template:sd-lora"], "widget": [{"text": "a <s0><s1> emoji dressed as an easter bunny", "output": {"url": "image_0.png"}}, {"text": "a <s0><s1> emoji dressed as an easte... | linoyts/huggy_lora_v2_pivotal | null | [
"diffusers",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"diffusers-training",
"text-to-image",
"lora",
"template:sd-lora",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
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#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #diffusers-training #text-to-image #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - linoyts/huggy_lora_v2_pivotal
<Gallery />
## Model description
### These are linoyts/huggy_lora_v2_pivotal LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
## Download model
### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
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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. -->
# Output_LayoutLMv3_1
This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlm... | {"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "microsoft/layoutlmv3-large", "model-index": [{"name": "Output_LayoutLMv3_1", "results": []}]} | BadreddineHug/Output_LayoutLMv3_1 | null | [
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"autotrain_compatible",
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| Output\_LayoutLMv3\_1
=====================
This model is a fine-tuned version of microsoft/layoutlmv3-large on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2963
* Precision: 0.8017
* Recall: 0.8407
* F1: 0.8207
* Accuracy: 0.9724
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": []} | lunarsylph/stableprep_v2 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
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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. -->
# pretrained-ai-or-not
This model is a fine-tuned version of [gusevvan/pretrained-ai-or-not](https://huggingface.co/gusevvan/pretr... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "gusevvan/pretrained-ai-or-not", "model-index": [{"name": "pretrained-ai-or-not", "results": []}]} | gusevvan/pretrained-ai-or-not | null | [
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] | null | 2024-04-01T17:53:25+00:00 | [] | [] | TAGS
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| pretrained-ai-or-not
====================
This model is a fine-tuned version of gusevvan/pretrained-ai-or-not on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1472
* Accuracy: 0.9804
Model description
-----------------
More information needed
Intended uses & limitation... | [
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text-classification | transformers |
# Model Card
## Model Description
We fine-tuned this [gelectra-large model](https://huggingface.co/deepset/gelectra-large) for four rounds of dynamic adversarial data collection to create the GAHD dataset. In each round annotators created examples by trying to trick the model into a misclassification. We explored di... | {"language": ["de"], "license": "cc-by-4.0", "library_name": "transformers", "tags": ["hate-speech-detection", "hate-speech"], "datasets": ["jagoldz/gahd", "Paul/hatecheck-german"], "metrics": ["f1"], "pipeline_tag": "text-classification"} | jagoldz/gahd | null | [
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|
# Model Card
## Model Description
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text-to-image | diffusers |
# ZavyComics
## b1
### Description:
> <p>First release.</p>
### Creator: Zavy
### Civitai Page: https://civitai.com/models/107613
You can use this with the [🧨Diffusers library](https://github.com/huggingface/diffusers)
### Diffusers
```py
from diff... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["Safetensors", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image"], "pipeline_tag": "text-to-image"} | sam749/ZavyComics-b1 | null | [
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"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | 2024-04-01T17:55:03+00:00 | [] | [] | TAGS
#diffusers #safetensors #Safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# ZavyComics
## b1
!Generated Sample
### Description:
> <p>First release.</p>
### Creator: Zavy
### Civitai Page: URL
You can use this with the Diffusers library
### Diffusers
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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. -->
# w2v2-base-pretrained_lr5e-5_at0.8_da0.8
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/fa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "w2v2-base-pretrained_lr5e-5_at0.8_da0.8", "results": []}]} | MelanieKoe/w2v2-base-pretrained_lr5e-5_at0.8_da0.8 | null | [
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#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-base #license-apache-2.0 #endpoints_compatible #region-us
| w2v2-base-pretrained\_lr5e-5\_at0.8\_da0.8
==========================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.2369
* Wer: 0.1717
Model description
-----------------
More information neede... | [
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text-generation | transformers |
# TW3-JRGL-v2
TW3-JRGL-v2 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [MTSAIR/MultiVerse_70B](https://huggingface.co/MTSAIR/MultiVerse_70B)
* [davidkim205/Rhea-72b-v0.5](https://huggingface.co/davidkim205/Rhea-72b-v0.5)
## 🧩 Configuration | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "MTSAIR/MultiVerse_70B", "davidkim205/Rhea-72b-v0.5"]} | paloalma/TW3-JRGL-v2 | null | [
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|
# TW3-JRGL-v2
TW3-JRGL-v2 is a merge of the following models using mergekit:
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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": []} | jneem/deepseek-coder-nickel | null | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me2-seqsight_4096_512_15M-L8
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_4096_512_15M-L8", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_4096_512_15M-L8 | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_4096\_512\_15M-L8
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6501
* F1 Score: 0.6111
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me2-seqsight_4096_512_15M-L32
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K4me2-seqsight_4096_512_15M-L32", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me2-seqsight_4096_512_15M-L32 | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_15M",
"region:us"
] | null | 2024-04-01T17:58:00+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K4me2-seqsight\_4096\_512\_15M-L32
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me2 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6494
* F1 Score: 0.615... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_4096_512_15M-L1
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_4096_512_15M-L1", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_4096_512_15M-L1 | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_15M",
"region:us"
] | null | 2024-04-01T17:58:50+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_4096\_512\_15M-L1
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6162
* F1 Score: 0.6557
* A... | [
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text-generation | transformers |
# MistralMerge-7B-stock
MistralMerge-7B-stock is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-Instruct-v0.2
- model: allknowingroger/JupiterMerge-7B-s... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit"]} | allknowingroger/MistralMerge-7B-stock | null | [
"transformers",
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"mistral",
"text-generation",
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"lazymergekit",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-01T17:58:51+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# MistralMerge-7B-stock
MistralMerge-7B-stock is a merge of the following models using LazyMergekit:
## Configuration
## Usage
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# w2v2-base-pretrained_lr5e-5_at0.8_da0.6
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/fa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "w2v2-base-pretrained_lr5e-5_at0.8_da0.6", "results": []}]} | MelanieKoe/w2v2-base-pretrained_lr5e-5_at0.8_da0.6 | null | [
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"wav2vec2",
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"base_model:facebook/wav2vec2-base",
"license:apache-2.0",
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"region:us"
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#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-base #license-apache-2.0 #endpoints_compatible #region-us
| w2v2-base-pretrained\_lr5e-5\_at0.8\_da0.6
==========================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3139
* Wer: 0.1773
Model description
-----------------
More information neede... | [
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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": []} | ManishThota/openchat_3.5-finetuned-adapters | null | [
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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. -->
# deepseek-coder-1.3b-instruct_max_steps_100_finetuned
This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-inst... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "deepseek-ai/deepseek-coder-1.3b-instruct", "model-index": [{"name": "deepseek-coder-1.3b-instruct_max_steps_100_finetuned", "results": []}]} | vdavidr/deepseek-coder-1.3b-instruct_max_steps_100_finetuned | null | [
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"base_model:deepseek-ai/deepseek-coder-1.3b-instruct",
"license:other",
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#peft #tensorboard #safetensors #llama #trl #sft #generated_from_trainer #base_model-deepseek-ai/deepseek-coder-1.3b-instruct #license-other #region-us
|
# deepseek-coder-1.3b-instruct_max_steps_100_finetuned
This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-instruct on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information need... | [
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text-generation | transformers |
# OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
<div align="center">
<img src="https://raw.githubusercontent.com/imoneoi/openchat/master/assets/logo_new.png" style="width: 65%">
</div>
<p align="center">
<a href="https://github.com/imoneoi/openchat">GitHub Repo</a> •
<a href="https://... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["openchat", "mistral", "C-RLFT"], "datasets": ["openchat/openchat_sharegpt4_dataset", "imone/OpenOrca_FLAN", "LDJnr/LessWrong-Amplify-Instruct", "LDJnr/Pure-Dove", "LDJnr/Verified-Camel", "tiedong/goat", "glaiveai/glaive-code-assistant", "meta-math/Meta... | ManishThota/openchat_3.5-finetuned | null | [
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"... | null | 2024-04-01T18:02:38+00:00 | [
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=======================================================================
[Online Demo](URL Repo</a> •
<a href=) •
[The first 7B model Achieves Comparable Results with ChatGPT (March)!
#1 Open-source model on MT-bench scorin... | [] | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_4096_512_15M-L8
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https://... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_4096_512_15M-L8", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_4096_512_15M-L8 | null | [
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"safetensors",
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_4096\_512\_15M-L8
============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6285
* F1 Score: 0.6482
* A... | [
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text-to-image | diffusers |
# RaekanaMix 2.5D
## v3.0
### Description:
> <p>Improved skin texture</p>
### Creator: Raelina
### Civitai Page: https://civitai.com/models/193551
You can use this with the [🧨Diffusers library](https://github.com/huggingface/diffusers)
### Diffusers
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] | null | 2024-04-01T18:04:19+00:00 | [] | [] | TAGS
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|
# RaekanaMix 2.5D
## v3.0
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> <p>Improved skin texture</p>
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### Civitai Page: URL
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | dipanjanS/distilbert-lora-finetuned-unmerged-imdb-sentiment | null | [
"transformers",
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"arxiv:1910.09700",
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"1910.09700"
] | [] | TAGS
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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visual-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. -->
# vilt_finetuned_fashion
This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co/dandelin/vilt-b32-ml... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "dandelin/vilt-b32-mlm", "model-index": [{"name": "vilt_finetuned_fashion", "results": []}]} | Ornelas/vilt_finetuned_fashion | null | [
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"base_model:dandelin/vilt-b32-mlm",
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|
# vilt_finetuned_fashion
This model is a fine-tuned version of dandelin/vilt-b32-mlm 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 hyperpara... | [
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text-generation | transformers |
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_pat... | {"license": "other", "library_name": "transformers", "tags": ["autotrain", "text-generation-inference", "text-generation", "peft"], "widget": [{"messages": [{"role": "user", "content": "What is your favorite condiment?"}]}]} | harrygens/autotrain-harrygens-sc3b | null | [
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"conversational",
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"has_space",
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] | null | 2024-04-01T18:06:18+00:00 | [] | [] | TAGS
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|
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit AutoTrain.
# Usage
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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"]} | Gonke/ppo-SnowballTarget | null | [
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# 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-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | lunarsylph/stablecell_v28 | null | [
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"region:us"
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers | <center><img src='https://i.imgur.com/dU9dUh0.png' width='500px'></center>
# Maxine-7B-0401-stock, an xtraordinary 7B model
**03-22-2024 - To date, louisbrulenaudet/Pearl-34B-ties is the "Best 🤝 base merges and moerges model of around 30B" on the Open LLM Leaderboard.**
## Configuration
```yaml
models:
- model... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "MTSAIR/multi_verse_model", "rwitz/experiment26-truthy-iter-0", "MaziyarPanahi/Calme-7B-Instruct-v0.2", "chemistry", "biology", "math"], "base_model": ["MTSAIR/multi_verse_model", "rwitz/experiment26-truthy-iter-... | louisbrulenaudet/Maxine-7B-0401-stock | null | [
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# Maxine-7B-0401-stock, an xtraordinary 7B model
03-22-2024 - To date, louisbrulenaudet/Pearl-34B-ties is the "Best base merges and moerges model of around 30B" on the Open LLM Leaderboard.
## Configuration
## Usage
## Citing & Authors
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text-classification | transformers |
# Model Card for remix-command-classifier-dbrt
<!-- Provide a quick summary of what the model is/does. -->
This model classifies text into the following categories:
- new_creation
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- nudge
## Model Details
English only, based on distilbert-base-uncased model
| {} | yregelman/remix-command-classifier-dbrt | null | [
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# Model Card for remix-command-classifier-dbrt
This model classifies text into the following categories:
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## Model Details
English only, based on distilbert-base-uncased model
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null | null | This is a llamafile for [BioMistral-7B-DARE](https://huggingface.co/BioMistral/BioMistral-7B-DARE) quantized to q5-k-m.
Safetensors came directly from their [source](https://huggingface.co/Nexusflow/Starling-LM-7B-beta/tree/main),
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-= Llamafile =-
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null | transformers |
# Uploaded model
- **Developed by:** cvzion
- **License:** apache-2.0
- **Finetuned from model :** Tensoic/TinyLlama-1.1B-3T-openhermes
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/u... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "gguf"], "base_model": "Tensoic/TinyLlama-1.1B-3T-openhermes"} | cvzion/gguf-TINYLLAMA-dqg-v1a-q4_k_m | null | [
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# Uploaded model
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | ziwenyd/ppo-LunarLander-v2-test | null | [
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|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
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null | 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": []} | areegtarek/idefics-9b-instruct-threesplitsthreeepochs-1-2-3 | null | [
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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. -->
# ABSA-SentencePair-DAPT-HARDSubsample60089-bert-base-Camel-MSA-ru2
This model is a fine-tuned version of [salohnana2018/CAMEL-dom... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "salohnana2018/CAMEL-domianAdaption-Single-ABSA-HardSample", "model-index": [{"name": "ABSA-SentencePair-DAPT-HARDSubsample60089-bert-base-Camel-MSA-ru2", "results": []}]} | salohnana2018/ABSA-SentencePair-DAPT-HARDSubsample60089-bert-base-Camel-MSA-ru2 | null | [
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| ABSA-SentencePair-DAPT-HARDSubsample60089-bert-base-Camel-MSA-ru2
=================================================================
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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": []} | zzttbrdd/sn6_09s | null | [
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text-to-image | diffusers |
# Real Dream
## 10 (legendary)
### Description:
>
### Creator: sinatra
### Civitai Page: https://civitai.com/models/153568
You can use this with the [🧨Diffusers library](https://github.com/huggingface/diffusers)
### Diffusers
```py
from diffusers ... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["Safetensors", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image"], "pipeline_tag": "text-to-image"} | sam749/Real-ream-10-legendary | null | [
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"safetensors",
"Safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | 2024-04-01T18:17:05+00:00 | [] | [] | TAGS
#diffusers #safetensors #Safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# Real Dream
## 10 (legendary)
!Generated Sample
### Description:
>
### Creator: sinatra
### Civitai Page: URL
You can use this with the Diffusers library
### Diffusers
| [
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text-generation | transformers |
# NeuralSpanish-7B-Stock
NeuralSpanish-7B-Stock is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
models:
- model: ecastera/ecastera-eva-westlake-7b-spanish
- model: Kukedlc/SpanishChat-7b
... | {"tags": ["merge", "mergekit", "lazymergekit"]} | Kukedlc/NeuralSpanish-7B-Stock | null | [
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|
# NeuralSpanish-7B-Stock
NeuralSpanish-7B-Stock is a merge of the following models using LazyMergekit:
## Configuration
## Usage
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] |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetune_starcoder2
This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b) ... | {"license": "bigcode-openrail-m", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "bigcode/starcoder2-3b", "model-index": [{"name": "finetune_starcoder2", "results": []}]} | samura1/finetune_starcoder2 | null | [
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"trl",
"sft",
"generated_from_trainer",
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"license:bigcode-openrail-m",
"region:us"
] | null | 2024-04-01T18:20:46+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #base_model-bigcode/starcoder2-3b #license-bigcode-openrail-m #region-us
|
# finetune_starcoder2
This model is a fine-tuned version of bigcode/starcoder2-3b 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 hyperparamet... | [
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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. -->
# cvt-13-finetuned-IDRiD
This model is a fine-tuned version of [microsoft/cvt-13](https://huggingface.co/microsoft/cvt-13) on an u... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "cvt-13-finetuned-IDRiD", "results": []}]} | SJChaudhuri/cvt-13-finetuned-IDRiD | null | [
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"generated_from_trainer",
"license:apache-2.0",
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"region:us"
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| cvt-13-finetuned-IDRiD
======================
This model is a fine-tuned version of microsoft/cvt-13 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2520
* Accuracy: 0.4524
Model description
-----------------
More information needed
Intended uses & limitations
-------... | [
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visual-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. -->
# blip_finetuned_fashion
This model is a fine-tuned version of [Salesforce/blip-vqa-base](https://huggingface.co/Salesforce/blip-v... | {"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "base_model": "Salesforce/blip-vqa-base", "model-index": [{"name": "blip_finetuned_fashion", "results": []}]} | Ornelas/blip_finetuned_fashion | null | [
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| blip\_finetuned\_fashion
========================
This model is a fine-tuned version of Salesforce/blip-vqa-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0916
Model description
-----------------
More information needed
Intended uses & limitations
--------------... | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sentiment-analysis-model
This model is a fine-tuned version of [dumitrescustefan/bert-base-romanian-cased-v1](https://huggingfac... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "dumitrescustefan/bert-base-romanian-cased-v1", "model-index": [{"name": "sentiment-analysis-model", "results": []}]} | nico-dv/sentiment-analysis-model | null | [
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| sentiment-analysis-model
========================
This model is a fine-tuned version of dumitrescustefan/bert-base-romanian-cased-v1 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2433
* Accuracy: 0.9151
* F1: 0.9151
Intended uses & limitations
--------------------------... | [
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null | transformers | # GGUF / IQ / Imatrix for [Cosmic-Citrus-9B](https://huggingface.co/ABX-AI/Cosmic-Citrus-9B)
**Why Importance Matrix?**
**Importance Matrix**, at least based on my testing, has shown to improve the ... | {"library_name": "transformers", "tags": ["mergekit", "merge", "not-for-all-audiences"], "base_model": ["ABX-AI/Cerebral-Infinity-7B", "ABX-AI/Spicy-Laymonade-7B"]} | ABX-AI/Cosmic-Citrus-9B-GGUF-IQ-Imatrix | null | [
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| # GGUF / IQ / Imatrix for Cosmic-Citrus-9B
!image/png
Why Importance Matrix?
Importance Matrix, at least based on my testing, has shown to improve the output and performance of "IQ"-type quantizations, where the compression becomes quite heavy.
The Imatrix performs a calibration, using a provided dataset. Testing ha... | [
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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": []} | giantdev/s27h61 | null | [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | dipanjanS/distilbert-lora-finetuned-merged-imdb-sentiment | null | [
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# Model Card for Model ID
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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. -->
# mDeBERTa-v3-base-mnli-xnli-finetune_v2
This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-mnli-xnli](https://h... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "MoritzLaurer/mDeBERTa-v3-base-mnli-xnli", "model-index": [{"name": "mDeBERTa-v3-base-mnli-xnli-finetune_v2", "results": []}]} | BishanSingh246/mDeBERTa-v3-base-mnli-xnli-finetune_v2 | null | [
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"deberta-v2",
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"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-01T18:30:49+00:00 | [] | [] | TAGS
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|
# mDeBERTa-v3-base-mnli-xnli-finetune_v2
This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-mnli-xnli on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training p... | [
"# mDeBERTa-v3-base-mnli-xnli-finetune_v2\n\nThis model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-mnli-xnli on the None dataset.",
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text-generation | transformers | # [MaziyarPanahi/Experiment24Experiment26-7B-GGUF](https://huggingface.co/MaziyarPanahi/Experiment24Experiment26-7B-GGUF)
- Model creator: [automerger](https://huggingface.co/automerger)
- Original model: [automerger/Experiment24Experiment26-7B](https://huggingface.co/automerger/Experiment24Experiment26-7B)
## Descrip... | {"tags": ["quantized", "2-bit", "3-bit", "4-bit", "5-bit", "6-bit", "8-bit", "GGUF", "transformers", "safetensors", "mistral", "text-generation", "merge", "mergekit", "lazymergekit", "automerger", "base_model:yam-peleg/Experiment24-7B", "base_model:rwitz/experiment26-truthy-iter-0", "license:cc-by-nc-4.0", "autotrain_c... | MaziyarPanahi/Experiment24Experiment26-7B-GGUF | null | [
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"base_model:rwitz/experiment26-truthy-iter-0"... | null | 2024-04-01T18:33:53+00:00 | [] | [] | TAGS
#transformers #gguf #mistral #quantized #2-bit #3-bit #4-bit #5-bit #6-bit #8-bit #GGUF #safetensors #text-generation #merge #mergekit #lazymergekit #automerger #base_model-yam-peleg/Experiment24-7B #base_model-rwitz/experiment26-truthy-iter-0 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text... | # MaziyarPanahi/Experiment24Experiment26-7B-GGUF
- Model creator: automerger
- Original model: automerger/Experiment24Experiment26-7B
## Description
MaziyarPanahi/Experiment24Experiment26-7B-GGUF contains GGUF format model files for automerger/Experiment24Experiment26-7B.
## How to use
Thanks to TheBloke for preparin... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - arkocharyan/aram-trained-xl-v2
<Gallery />
## Model description
These are arkocharyan/aram-tra... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "lora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"], "base_model": "SG161222/RealVisXL_V4.0", "instance_prompt": "A photo of zwx", "widget": [{"text": "A p... | arkocharyan/aram-trained-xl-v2 | null | [
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"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:SG161222/RealVisXL_V4.0",
"license:openrail++",
"region:us"
] | null | 2024-04-01T18:34:08+00:00 | [] | [] | TAGS
#diffusers #tensorboard #text-to-image #diffusers-training #lora #template-sd-lora #stable-diffusion-xl #stable-diffusion-xl-diffusers #base_model-SG161222/RealVisXL_V4.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - arkocharyan/aram-trained-xl-v2
<Gallery />
## Model description
These are arkocharyan/aram-trained-xl-v2 LoRA adaption weights for SG161222/RealVisXL_V4.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyol... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K9ac-seqsight_4096_512_15M-L32
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K9ac-seqsight_4096_512_15M-L32", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K9ac-seqsight_4096_512_15M-L32 | null | [
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"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K9ac-seqsight\_4096\_512\_15M-L32
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K9ac dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6684
* F1 Score: 0.6475
*... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 20000",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-seqsight_4096_512_15M-L1
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_4096_512_15M-L1", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_4096_512_15M-L1 | null | [
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"region:us"
] | null | 2024-04-01T18:37:58+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_4096\_512\_15M-L1
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6764
* F1 Score: 0.5634
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-seqsight_4096_512_15M-L8
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:/... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_4096_512_15M-L8", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_4096_512_15M-L8 | null | [
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"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_15M",
"region:us"
] | null | 2024-04-01T18:38:12+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_4096\_512\_15M-L8
=============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6830
* F1 Score: 0.5741
... | [
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text-generation | transformers | # my-first-blend
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 [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using mistralai/Mistral-7B-Instruct-v0.2 as a base.
### Mode... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["mistralai/Mistral-7B-Instruct-v0.2"], "model-index": [{"name": "my-first-blend", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", ... | pandego/my-first-blend | null | [
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"license:apache-2.0",
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"regi... | null | 2024-04-01T18:39:16+00:00 | [
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| my-first-blend
==============
This is a merge of pre-trained language models created using mergekit.
Merge Details
-------------
### Merge Method
This model was merged using the task arithmetic merge method using mistralai/Mistral-7B-Instruct-v0.2 as a base.
### Models Merged
The following models were inclu... | [
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text-to-image | diffusers |
# SDXL LoRA DreamBooth - linoyts/huggy_lora_edm_v3_pivotal
<Gallery />
## Model description
### These are linoyts/huggy_lora_edm_v3_pivotal LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
## Download model
### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- **LoRA**: downlo... | {"license": "openrail++", "tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "diffusers-training", "text-to-image", "diffusers", "lora", "template:sd-lora", "edm-training"], "inference": {"parameters": {"scheduler": "EulerDiscreteScheduler"}}, "widget": [{"text": "a <s0><s1> emoji dressed as an easter bun... | linoyts/huggy_lora_edm_v3_pivotal | null | [
"diffusers",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"diffusers-training",
"text-to-image",
"lora",
"template:sd-lora",
"edm-training",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
] | null | 2024-04-01T18:39:38+00:00 | [] | [] | TAGS
#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #diffusers-training #text-to-image #lora #template-sd-lora #edm-training #base_model-stabilityai/stable-diffusion-xl-base-1.0 #license-openrail++ #region-us
|
# SDXL LoRA DreamBooth - linoyts/huggy_lora_edm_v3_pivotal
<Gallery />
## Model description
### These are linoyts/huggy_lora_edm_v3_pivotal LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
## Download model
### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- LoRA: download '... | [
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text-to-image | diffusers |
# fennfoto
## ff2
### Description:
>
### Creator: Fenn
### Civitai Page: https://civitai.com/models/153869
You can use this with the [🧨Diffusers library](https://github.com/huggingface/diffusers)
### Diffusers
```py
from diffusers import StableDif... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["Safetensors", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image"], "pipeline_tag": "text-to-image"} | sam749/fennfoto-ff2 | null | [
"diffusers",
"safetensors",
"Safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | null | 2024-04-01T18:39:56+00:00 | [] | [] | TAGS
#diffusers #safetensors #Safetensors #stable-diffusion #stable-diffusion-diffusers #text-to-image #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# fennfoto
## ff2
!Generated Sample
### Description:
>
### Creator: Fenn
### Civitai Page: URL
You can use this with the Diffusers library
### Diffusers
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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. -->
# q1
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on an unknown dat... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "distilbert/distilgpt2", "model-index": [{"name": "q1", "results": []}]} | samhitmantrala/q1 | null | [
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"base_model:distilbert/distilgpt2",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
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| q1
==
This model is a fine-tuned version of distilbert/distilgpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0078
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Train... | [
"### 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: 20",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H3K4me3-seqsight_4096_512_15M-L32
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https:... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H3K4me3-seqsight_4096_512_15M-L32", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H3K4me3-seqsight_4096_512_15M-L32 | null | [
"peft",
"safetensors",
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"base_model:mahdibaghbanzadeh/seqsight_4096_512_15M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H3K4me3-seqsight\_4096\_512\_15M-L32
==============================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H3K4me3 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6806
* F1 Score: 0.570... | [
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null | null |
4-bit [OmniQuant](https://arxiv.org/abs/2308.13137) quantized version of [Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta).
| {"license": "apache-2.0"} | numen-tech/Starling-LM-7B-beta-w4a16g128asym | null | [
"arxiv:2308.13137",
"license:apache-2.0",
"region:us"
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"2308.13137"
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#arxiv-2308.13137 #license-apache-2.0 #region-us
|
4-bit OmniQuant quantized version of Starling-LM-7B-beta.
| [] | [
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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. -->
# connections-generator-finetuned
This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-comm... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "openai-community/gpt2", "model-index": [{"name": "connections-generator-finetuned", "results": []}]} | anishthalamati/connections-generator-finetuned | null | [
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] | null | 2024-04-01T18:43:57+00:00 | [] | [] | TAGS
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| connections-generator-finetuned
===============================
This model is a fine-tuned version of openai-community/gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0643
Model description
-----------------
More information needed
Intended uses & limitations
---... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_4096_512_15M-L1
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H4-seqsight_4096_512_15M-L1", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_4096_512_15M-L1 | null | [
"peft",
"safetensors",
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H4-seqsight\_4096\_512\_15M-L1
========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4892
* F1 Score: 0.7847
* Accuracy: 0.7... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 20000",
... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_4096_512_15M-L32
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https://hug... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H4-seqsight_4096_512_15M-L32", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_4096_512_15M-L32 | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_15M",
"region:us"
] | null | 2024-04-01T18:44:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H4-seqsight\_4096\_512\_15M-L32
=========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5554
* F1 Score: 0.7742
* Accuracy: 0... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GUE_EMP_H4-seqsight_4096_512_15M-L8
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_15M](https://hugg... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_15M", "model-index": [{"name": "GUE_EMP_H4-seqsight_4096_512_15M-L8", "results": []}]} | mahdibaghbanzadeh/GUE_EMP_H4-seqsight_4096_512_15M-L8 | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_15M",
"region:us"
] | null | 2024-04-01T18:44:23+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_15M #region-us
| GUE\_EMP\_H4-seqsight\_4096\_512\_15M-L8
========================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_15M on the mahdibaghbanzadeh/GUE\_EMP\_H4 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4782
* F1 Score: 0.7789
* Accuracy: 0.7... | [
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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": []} | Raghav3842/mistral_7b_aptus | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-01T18:50:47+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
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-Documentati... | {"library_name": "ml-agents", "tags": ["Pyramids", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | Gonke/ppo-Pyramids | null | [
"ml-agents",
"tensorboard",
"onnx",
"Pyramids",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | null | 2024-04-01T18:51:36+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids
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 ... | [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\n\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n - A *short tutori... | [
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"TAGS\n#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\... |
reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-Pixelcopter-PLE-v0", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelco... | lbaeriswyl/Reinforce-Pixelcopter-PLE-v0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-01T18:55:21+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
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"TAGS\n#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of the De... |
image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-base
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-b... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swin-base-patch4-window7-224", "model-index": [{"name": "swin-base", "results": []}]} | gusevvan/swin-base | null | [
"transformers",
"tensorboard",
"safetensors",
"swin",
"image-classification",
"generated_from_trainer",
"base_model:microsoft/swin-base-patch4-window7-224",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-01T18:56:26+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #swin #image-classification #generated_from_trainer #base_model-microsoft/swin-base-patch4-window7-224 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| swin-base
=========
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0891
* Accuracy: 0.9804
Model description
-----------------
More information needed
Intended uses & limitations
-----------... | [
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