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MiniLM-v2

Lightweight sentence embedding model for semantic similarity and search.

All‑MiniLM‑L6‑v2 maps sentences to a 384‑dimensional dense vector space. Trained on 1B+ sentence pairs, it excels at semantic search, clustering, and sentence similarity tasks while being small enough to run on mobile devices.

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Model RepositoryHugging FaceResearch Paper

Technical Details

Model checkpoint:sentence-transformers/all-MiniLM-L6-v2
Input resolution:128 tokens
Number of parameters:22.7M
Model size (float):86.7 MB
Embedding dimension:384

Applicable Scenarios

  • Semantic Search
  • Text Classification
  • Clustering

License

Model:APACHE-2.0

Tags

  • foundation
  • real-time

Supported Compute Devices

  • Snapdragon X Elite CRD
  • Snapdragon X Plus 8-Core CRD
  • Snapdragon X2 Elite CRD

Supported Compute Chipsets

  • Snapdragon® X Elite
  • Snapdragon® X Plus 8-Core
  • Snapdragon® X2 Elite

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