Model reference · open weights

msmarco-distilbert-cos

msmarco-distilbert-cos is an open-weight embedding model from sentence-transformers, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Licence fee required Embeddings sentence-transformers 1 variants 133k downloads/mo
Request a licence + hosting quote All served models Not on the shared API today — deployed on request.

About

What msmarco-distilbert-cos is

msmarco-distilbert-cos-v5 This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and was designed for semantic search. It has been trained on 500k (query, answer) pairs from the MS MARCO Passages dataset. For an introduction to semantic search, have a look at: SBERT.net - Semantic Search Usage (Sentence-Transformers) Using this model becomes easy when you have sentence-transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) 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. Technical Details In the following some technical details how this model must be used: Note: When loaded with sentence-transformers, this model produces normalized embeddings with length 1. In that case, dot-product and cosine-similarity are equivalent. dot-product is preferred as it is faster. Euclidean distance is proportional to dot-product and can also be used. Citing & Authors This model was trained by sentence-transformers. If you find this model helpful, feel free to cite our publication Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks:

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makersentence-transformers
TypeEmbedding models
Parameters (lead)66M
Context512 tokens
Variants1
Runs withsentence-transformers
Released2022-03-02
Popularity133k downloads / month
Likes10
LicenceCommercial licence needed

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together — the basis of search and RAG.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
msmarco-distilbert-cos-v566MBF16~0.2 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys msmarco-distilbert-cos for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (msmarco-distilbert-cos below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"msmarco-distilbert-cos","input":"text to embed"}'

Details

Languages, data & research

Languages

en

Tags

sentence-transformers pytorch tf onnx safetensors openvino distilbert feature-extraction sentence-similarity transformers en text-embeddings-inference endpoints_compatible deploy:azure

Papers

Licence

Commercial licence needed

The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗

Sources

Weights & code

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