zjunlp/OneGen
[EMNLP 2024] OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs.
OneGen helps AI developers efficiently fine-tune large language models (LLMs) for tasks that involve both generating text and finding relevant information. It takes an LLM and training data for specific tasks like answering questions or linking entities, and produces a single, optimized LLM ready for deployment. This is for AI/ML engineers and researchers who are building applications that require LLMs to generate accurate responses by retrieving information.
147 stars. No commits in the last 6 months.
Use this if you need to fine-tune LLMs for retrieval-augmented generation (RAG) tasks and want to reduce model deployment and inference costs by using a single model.
Not ideal if you are looking for an out-of-the-box, no-code solution for end-user applications, as this project requires developer expertise to implement.
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147
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15
Language
Python
License
MIT
Category
Last pushed
Nov 13, 2024
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