yuchenlin/LLM-Blender
[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths of multiple open-source LLMs. LLM-Blender cut the weaknesses through ranking and integrate the strengths through fusing generation to enhance the capability of LLMs.
This project helps anyone working with large language models (LLMs) to get better results by combining the strengths of multiple models. You input a prompt and several different LLM responses, and it outputs a refined, higher-quality response. This is for AI practitioners, content creators, researchers, and developers who want to improve the outputs of open-source LLMs.
976 stars. No commits in the last 6 months.
Use this if you are using open-source large language models and want to consistently achieve superior performance by blending their best aspects into one high-quality output.
Not ideal if you are only working with a single LLM and are not interested in comparing or fusing multiple outputs.
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976
Forks
88
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 22, 2024
Commits (30d)
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