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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