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.
Not supported
This model is currently not supported on any IoT chipset.
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View for other chipsetsTechnical 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 IoT Devices
- Dragonwing IQ-8275 EVK
- Dragonwing IQ-9075 EVK
- Dragonwing IQ-X5121
- Dragonwing IQ-X7181
- Dragonwing Q-6690 MTP
- Dragonwing Q-7790
- Dragonwing Q-8750
- Dragonwing RB3 Gen 2 Vision Kit
- QCS8550 (Proxy)
Supported IoT Chipsets
- Qualcomm® QCM6690
- Qualcomm® QCS6490
- Qualcomm® QCS7181
- Qualcomm® QCS7790
- Qualcomm® QCS8275
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® QCS8750
- Qualcomm® QCS9075
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