FareedKhan-dev/Solve-LLM-Knowledge-Cutoff
A Classification Approach: Making LLM Knowledge-Aware
This project helps individual developers overcome the 'knowledge cutoff' limitation of large language models (LLMs). By classifying user prompts and fetching up-to-date information from external APIs, it enables LLMs to answer questions about current events. The system takes a user's question as input and outputs a more informed answer from the LLM, making it useful for anyone deploying LLM-powered applications.
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Use this if you need your LLM to answer questions about recent events, news, or evolving topics without relying on expensive Retrieval Augmented Generation (RAG) solutions.
Not ideal if your application strictly requires knowledge only up to the LLM's original training data or if you have the resources for a full-scale RAG implementation.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Jan 29, 2024
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