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