Helper application for building search indexes with pyserini
Project description
pyserini-indexer
Helper application for building index files that uses pyserini
Prerequisites
- python 3.9 (pytorch + faiss are only working under this version unfortunaly ☹️ )
- if you would want to create/search using learnable Sparse indexes (UNICOIL), you would need CUDA support (pyserini requires here CUDA for backend 😞)
Indexing methods:
- Sparse:
- BM25 - traditional not-learnable indexing technique
- UNICOIL - uses LuceneImpact underneath
- Dense:
- MINILM_V2 - smallest model available
- ANCE
- TCT_COLBERT - biggest (0.5 gb) and provides best results
Backend support
By default all indexing methods use CPU. If you would want to change this behaviour, set environment variable USE_GPU to some value.
Example usage
- Create BM25 sparse index directory
python pyserini-indexer BM25 index_input -o tests/indexes/bm25
- Create dense index directory
python pyserini-indexer MINILM_V2 index_input -o tests/indexes/minilm_v2
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