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
Evaluation of BEIR Datasets using ColBERT retrieval model
Efficient late-interaction retrieval systems in Julia!
Official codebase for the ACL 2025 Findings paper: Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval.
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
Open source ColBERT based document database
Index GitHub repositories to ColBERT models and serve them with GRPC or FastAPI
A Powerful Python Library to Build AI Applications with the RAG
This is the Information Retrieval 2023-2024 fall semester CEID course project.
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