Story Generation Using GPT-2 in Hugging Face
This repository provides an example of how to use the GPT-2 language model in Hugging Face for story generation tasks. GPT-2 is a powerful natural language processing model that can generate human-like text, and Hugging Face is a popular open-source library for working with NLP models.
Requirements
- Python 3.6 or higher
- Hugging Face transformers library
- PyTorch or TensorFlow
Installation
- Clone this repository: git clone
https://github.com/BaoToan1704/Deep-Learning/Final%20Project
- Navigate to the repository directory:
cd Final Project
- Install the required libraries:
pip install -r requirements.txt
Usage
- Download the GPT-2 pre-trained model:
python download_model.py
- Edit the
Gpt_2_to_generate_stories.ipynb
file to include your desired prompt and generate settings. - Run the
Gpt_2_to_generate_stories.ipynb file
to generate text:python Gpt_2_to_generate_stories.ipynb
Customization
You can customize the GPT-2 model and the text generation settings by editing the Gpt_2_to_generate_stories.ipynb
file. For example, you can change the prompt text, the number of tokens to generate, the temperature setting for the model, and more.
References
- Hugging Face Transformers library:
https://github.com/huggingface/transformers
- GPT-2 model by me:
https://huggingface.co/baotoan2002/GPT-2
- OpenAI GPT-2 model:
https://openai.com/models/gpt-2/
License
This repository is licensed under the [openrail] License. See the LICENSE file for details.
Acknowledgments
- Special thanks to the Hugging Face team for their excellent work on the Transformers library.
- Thanks to OpenAI for providing the pre-trained GPT-2 model.
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