https://github.com/skylark0924/huggingface-finetune-tutorial
https://github.com/skylark0924/huggingface-finetune-tutorial
Last synced: 8 months ago
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- Host: GitHub
- URL: https://github.com/skylark0924/huggingface-finetune-tutorial
- Owner: Skylark0924
- Created: 2023-05-26T13:15:22.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-05-31T04:24:13.000Z (over 2 years ago)
- Last Synced: 2024-11-30T02:46:08.477Z (10 months ago)
- Language: Python
- Size: 54.7 KB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# HuggingFace-finetune-tutorial
In this tutorial, we summarized all pre-trained models supported by HuggingFace, and provided the finetuning code for
each model. The models are divided into 4 task categories:
- Natural Language Processing (NLP)
- Computer Vision (CV)
- Audio Processing (AP)
- Multi-Modal (MModal)
## Install
```
git clone https://github.com/Skylark0924/HuggingFace-finetune-tutorial
cd HuggingFace-finetune-tutorial
pip install -r requirements.txt
```
## Usage
### Sign up HuggingFace and add your API token
1. Sign up HuggingFace: https://huggingface.co/join
2. Create and copy your API token: https://huggingface.co/settings/tokens
3. Add your API token to `token.txt` under the root directory of this repository
### Fine-tune a model
Fine-tune a model is very easy, just run the file related to your interested task.
For example, if you want to fine-tune a model for text classification, just run the following command:
```
cd NLP
python text_classification_finetune.py
```
> **Note**
> If you want to fine-tune a model on your own dataset, please modify the `dataset` variable in the file. And you
> can also use specific model by modifying the `pre_trained_model` variable.