This project is designed to help you learn fundamental concepts of Artificial Intelligence, focusing on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). The project provides hands-on experience with popular AI tools and frameworks.
- LLM Integration using Hugging Face Transformers
- RAG Implementation for document retrieval and Q&A
- Vector Store management
- Document processing capabilities
- Neural Heat-Map
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Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows: .\venv\Scripts\activate
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Install dependencies:
pip install -r requirements.txt
or setup.py install
pip setup.py install
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LLM Basics
- Understanding transformer architecture
- Using pre-trained models
- Fine-tuning for specific tasks
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RAG Implementation
- Document processing
- Vector embeddings
- Retrieval mechanisms
- Question answering
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Advanced Topics
- Custom model training
- Performance optimization
Check the examples/ directory for practical demonstrations of each concept.
Run unit tests:
python -m unittest discover tests/Feel free to contribute by:
- Adding new examples
- Improving documentation
- Fixing bugs
- Suggesting enhancements
MIT License