sentence-transformers/multi-qa-MiniLM-L6-dot-v1
sentence-similarity model by sentence-transformers
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Model card & documentation
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This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and was designed for semantic search. It has been trained on 215M (question, answer) pairs from diverse sources. For an introduction to semantic search, have a look at: SBERT.net - Semantic Search Using this model becomes easy when you have sentence-transformers installed: Then you can use the model like this: Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the correct pooling-operation on-top of the contextualized word embeddings. In the following some technical details how this model must be used: The project aims to train sentence embedding models on very large sentence level datasets using a self-supervised contrastive learning objective. We use a contrastive learning objective: given a sentence from the pair, the model should predict which out of…
Read the full model card ↗ · Preview checked 2026-10-06T06:42:02.004Z
Inside the original model card — Document outline
- multi-qa-MiniLM-L6-dot-v1
- Usage (Sentence-Transformers)
- Usage (HuggingFace Transformers)
- Technical Details
- Background
- Intended uses
- Training procedure
- Pre-training
- Training
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Model overview
sentence-transformers/multi-qa-MiniLM-L6-dot-v1 is a sentence-similarity model repository published by sentence-transformers on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 118,198
- Cumulative likes
- 17
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 22,713,728
- Architecture
- BertModel
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2024-11-05T20:22:38.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-06T06:41:57.048Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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