This project provides a comprehensive benchmarking framework for evaluating RAG (Retrieval-Augmented Generation) performance using Qwen3 embedding and reranker models of different sizes (0.6B, 4B, 8B) ...
Built on Eric Buess's excellent foundation, this fork adds Python-powered search, validation, and auto-regeneration features while maintaining graceful degradation - everything works with or without ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results