How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code
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Papers with Code uses Hugging Face services to build an intelligent search system for AI research papers.
The system combines two search methods — exact word matching and semantic search that understands meaning — to find relevant papers even when words don't appear together. Hugging Face Jobs runs the heavy computation to create vectors from all 110,000 papers, Storage Buckets stores intermediate results, and Inference Endpoints keep the search fast for user queries. If the search service doesn't respond, the system automatically falls back to standard text search.
Keyword search finds exact mentions, whereas vector search finds more fuzzy, semantically similar terms.
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