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facebookresearch/dpr-scale ★ 297 33 DATA_RESEARCH

This repository is a research codebase for implementing and experimenting with dense retrieval techniques. It provides implementations of multiple advanced retrieval models including DPR, CITADEL, COIL, ColBERT, SPLADE, and their variants, along with data augmentation strategies like DRAGON and DRAMA. The codebase enables researchers to train, evaluate, and compare different retrieval approaches on standard benchmarks like Natural Questions, MS MARCO, and conversational datasets. It features a modular architecture with separate components for data processing, model definitions, training tasks, and evaluation, configured through Hydra for easy experimentation.

RATING: 7.8/10 REPRO: 6.0/10 MAINT: active DRIFT: high
#dense-retrieval #question-answering #embedding-generation #data-augmentation #multi-vector-retrieval #sparse-dense-hybrid #distillation #mrr-optimization
▸ 4 reusable components found
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