zekaouinoureddine/Adding-Private-Data-to-LLMs
RAG - Add Your Own Data to LLMs Using LangChain & LlamaIndex
This project helps you get answers from large language models (LLMs) using your own specific, up-to-date, or private documents. You provide your documents and then ask questions, receiving answers that are informed by your provided data rather than just the general knowledge the LLM was originally trained on. This is for anyone who needs to query an LLM about information not publicly available or very recent, such as internal company reports or specialized research papers.
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Use this if you need an LLM to answer questions using your specific, proprietary, or recently updated documents, going beyond its general pre-2021 knowledge.
Not ideal if you only need answers based on general knowledge readily available on the public internet, as this adds the complexity of managing your own data.
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Jupyter Notebook
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Last pushed
Apr 06, 2024
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