NovaSearch-Team/RAG-Retrieval
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
Supports knowledge distillation from larger models (including 7B+ LLMs) into compact variants like BERT-base or 0.5B LLMs, and implements advanced training techniques like MRL loss and preference-based fine-tuning. Provides a unified inference library (`rag-retrieval` pip package) with a consistent API across heterogeneous reranker architectures (cross-encoders, decoder-only LLMs) and flexible long-document handling strategies. Integrates with popular open-source models (BGE, BCE, GTE) and supports distributed training via DeepSpeed and FSDP.
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1,103
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Language
Python
License
MIT
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Last pushed
Jul 05, 2025
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