Better Llama 2 with Retrieval Augmented Generation (RAG)

Retrieval Augmented Generation (RAG) allows us to keep our Large Language Models (LLMs) up to date with the latest information, reduce hallucinations, and allow us to cite the original source of information being used by the LLM.

We build the RAG pipeline using a Pinecone vector database, a Llama 2 13B chat model, and wrap everything in Hugging Face and LangChain code.

📌 Code:
https://github.com/pinecone-io/examples/blob/master/learn/generation/llm-field-guide/llama-2-13b-retrievalqa.ipynb

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👋🏼 AI Consulting:
https://aurelio.ai

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https://discord.gg/c5QtDB9RAP …

build chat database hallucinations information language language models large language large language models llama llama 2 llm llms pinecone pipeline reduce retrieval retrieval augmented generation up to date vector vector database