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Angshul/SparseGeometricRAG

SparseGeometricRAG CPU-first sparse geometric retrieval for practical top-10 RAG No transformer inference at retrieval time. No retrieval GPU requirement. No dense document-vector dot products. No external API. SparseGeometricRAG is a retrieval system built around one systems objective: make the retrieval layer cheap enough to run on ordinary multicore CPU hardware without turning the corpus into a dense embedding database. It uses sparse TF-IDF geometry, fuzzy… See the full description on the dataset page: https://huggingface.co/datasets/Angshul/SparseGeometricRAG.

sourceHugging Facefair-noncommercial-research-licenseupdated 2mo agoView on Hugging Face
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README.md21 linesDownload Raw Back to data
1# Data2 3Datasets are intentionally not committed to the repository.4 5The code accepts either an extracted standard BEIR directory or a standard BEIR `.zip` containing:6 7```text8corpus.jsonl9queries.jsonl10qrels/test.tsv11```12 13Examples used in the current repository:14 15```text16data/scifact.zip17data/trec-covid.zip18```19 20For full MS MARCO scale reproduction, follow `docs/REPRODUCIBILITY.md` and the shard manifest in `manifests/`.21