This Python project harnesses the power of the GPT-2 model from Hugging Face for text generation. It utilizes the LLM (Language Model Layer) library and the langchain for language processing, creating an environment where you can easily generate human-like text content.
- Hugging Face Transformers (for GPT-2 model)
- LLM (Language Model Layer)
- dotenv (for environment variable configuration)
- langchain (for language processing)
- Text Generation: The script can generate text content based on prompts provided.
- Customizable Output: Users can specify the length, style, and tone of the generated text.
- Integration of GPT-2: It employs the GPT-2 model from Hugging Face, known for its text generation capabilities.
- Easy Configuration: Environment variables (dotenv) are used for easy configuration and management.
Before running the script, make sure you have the following libraries installed:
- Python 3.x
- Hugging Face Transformers
- LLM
- dotenv
- langchain
You can install these libraries using pip:
pip install transformers llm python-dotenv langchain##Usage
- Clone this repository to your local machine:
git clone https://github.com/mrnithish/gpt2-huggingface-llm.git- Navigate to the project directory:
cd gpt2-huggingface-llm- Configure your environment variables by creating a .env file with the necessary settings. An example .env file might look like this:
HUGGING_FACE_API_KEY=your_hugging_face_api_key- Run the Python script:
python gpt2.py- Follow the prompts to specify the text generation parameters, including length and style.
- The generated text will be displayed in the console.
Customization
You can customize the script to handle specific text generation tasks or language processing requirements by modifying the text_generation.py script.
License
This project is licensed under the MIT Licence . See the LICENSE.md file for details.