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A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

MTEB: Massive Text Embedding Benchmark

Fastrag ⭐ 591

Efficient Retrieval Augmentation and Generation Framework

Simple NLP in Rust with Python bindings

A large-scale multilingual dataset for Information Retrieval. Thorough human-annotations across 18 diverse languages.

Deep Learning Hard (DL-HARD) is a new annotated dataset extending TREC Deep Learning benchmark.

Heterogenous, Task- and Domain-Specific Benchmark for Unsupervised Sentence Embeddings used in the TSDAE paper: https://arxiv.org/abs/2104.06979.

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