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Embedding models convert text into high-dimensional vectors for semantic search, similarity comparisons, and other vector-based operations.

Nomic
Nomic Embed Text v1.5
nomic-embed-text
Dimensions: 768Strengths: Long-context embeddings, Matryoshka dimensionalityBest for: Semantic search, document similarity, clusteringConfiguration repo: tinfoilsh/confidential-nomic-embed-text