This project offers a reference implementation that combines document retrieval with a large language model like Llama, allowing users to ask questions and receive answers based on a knowledge base. You can also replace the large language model inference with OpenAI APIs for even better performance.
setup.sh provide a reference implementation for initializing the model.embedding_retrieval.py provides embedding based retrieval capability, and llama_model.py provides the Q&A capability based on Alpaca-LoRA.embedding_retrieval.py.This project offers a reference implementation that combines document retrieval with a large language model like Llama, allowing users to ask questions and receive answers based on a knowledge base. You can also replace the large language model inference with OpenAI APIs for even better performance.
setup.sh provide a reference implementation for initializing the model.embedding_retrieval.py provides embedding based retrieval capability, and llama_model.py provides the Q&A capability based on Alpaca-LoRA.embedding_retrieval.py.