NovaSearch-Team / RAG-Retrieval

What it does

• Simple yet Elegant. Rejects complex, with a simple and understandable code structure for easy modifications.
• Supports end-to-end fine-tuning of RAG retrieval models: Embedding (bert-based, llm-based), late interaction models (colbert), and reranker models (bert-based, llm-based).
• Supports fine-tuning of any open-source RAG retrieval models: Compatible with most open-source embedding and reranker models, such as: bge (bge-embedding, bge-m3, bge-reranker), bce (bce-embedding, bce-reranker), gte (gte-embedding, gte-mul
• Supports distillation of larger models into smaller models: Enables the distillation of larger LLM-based reranker or embedding models into smaller ones (e.g., a 0.5B-parameter LLM or BERT-base).
• Advanced Algorithms. For embedding models, supports the MRL algorithm to reduce the dimensionality of output vectors and Stella distillation method.