Embedding
Embedding numeric vector ne da ke wakiltar ma'anar rubutu, hotuna, ko wasu data a high-dimensional space. Abubuwan da ke da ma'ana makamanciya suna samar da vectors da ke kusa da juna, abin da ke ba systems damar compare, cluster, da retrieve content ta semantic similarity maimakon exact matches.
Kalmomi masu kama: vector embedding, text embedding, semantic vector, dense representation
Embeddings gada ce tsakanin harshen mutum da lissafin similarity. Embedding model yana mayar da kowace input zuwa fixed-length vector domin items masu alaka ta ma’ana su taru kusa, yana ba da damar vector search, clustering, classification, da deduplication. A retrieval pipeline, indexed chunks da incoming query ana embed dinsu da model guda domin distances su kasance masu ma’ana. Saboda embedding model ne ke fayyace space din, version dinsa metadata ne da ya cancanci tracking don reproducibility da controlled reindexing.