A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
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Updated
Jun 4, 2025 - Python
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Efficient Retrieval Augmentation and Generation Framework
🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
Late Interaction Models Training & Retrieval
Neural Search
High-Performance Engine for Multi-Vector Search
ColBERT humor dataset for the task of humor detection, containing 200,000 jokes/news
An easy-to-use python toolkit for flexibly adapting various neural ranking models to target domain.
Vector Database with support for late interaction and token level embeddings.
Tree-based indexes for neural-search
Official codebase for the ACL 2025 Findings paper: Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval.
Evaluation of BEIR Datasets using ColBERT retrieval model
Efficient late-interaction retrieval systems in Julia!
A list of multi-vector retrieval resources
A demonstration of hybrid search with reranking using Qdrant and BGE-M3 model. A showcase of dense and sparse retrieval combined with ColBERT reranking for optimal search results
An overview of popular reranking models and architectures for 2 stage RAG pipelines
Boost RAG performance with question decomposer
Open source ColBERT based document database
Index GitHub repositories to ColBERT models and serve them with GRPC or FastAPI
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