sentence-transformers / sentence-similarity updated 1 year ago

multi-qa-MiniLM-L6-cos-v1

Name: multi-qa-MiniLM-L6-cos-v1
Author: sentence-transformers

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

Params

20 M

Context

512

Downloads 30d

882 K

Likes

138

Licence: unknown Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

897 K826 K

Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f32	0.1 GB	0.6 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Architecture: BertModel
Parameters: 20 M
Tensor type: F32
Context length: 512
Vocabulary: 30,522
Layers / heads: 6 / 12
First seen on the Hub: 2022-03-02
Training datasets: flax-sentence-embeddings/stackexchange_xml, ms_marco, gooaq, yahoo_answers_topics, search_qa, eli5, natural_questions, trivia_qa, embedding-data/QQP, embedding-data/PAQ_pairs, embedding-data/Amazon-QA, embedding-data/WikiAnswers
Added to our catalog: 2026-07-28

Compare with

all-MiniLM-L6-v2 257.8 M paraphrase-multilingual-MiniLM-L12-v2 59.4 M bge-m3 35.0 M all-mpnet-base-v2 25.2 M paraphrase-MiniLM-L6-v2 2.8 M paraphrase-MiniLM-L3-v2 2.6 M

Appears in

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