FareedKhan-dev/Improve-Weak-LLM-Using-SPIN-Technique
After RLHF and SFT show promising results, a new technique named SPIN is invented for 2024
This project helps improve a weaker Large Language Model (LLM) using a technique called SPIN, without needing more human-annotated data. You input an existing LLM that has been fine-tuned with supervised learning, and the output is a more capable LLM that generates responses almost indistinguishable from human-written text. This is for researchers and developers working on enhancing LLMs, particularly those facing constraints on human annotation resources.
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Use this if you have a base LLM that has undergone supervised fine-tuning and want to significantly improve its performance and human-like response generation without requiring extensive new human annotations.
Not ideal if you are looking for an initial training method for an LLM from scratch or if you have ample human-annotated data available for traditional fine-tuning methods like RLHF.
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Jan 17, 2024
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