Model reference · open weights

UNI2-h

UNI2-h is an open-weight embedding model from MahmoodLab, 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 MahmoodLab 1 variants 73k downloads/mo
Request a licence + hosting quote All served models Not on the shared API today — deployed on request.

Specifications

What it is

MakerMahmoodLab
TypeEmbedding models
Variants1
Runs withtimm
Released2025-01-10
Popularity73k downloads / month
Likes170
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
UNI2-hBF16Weights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys uni2-h for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (uni2-h 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":"uni2-h","input":"text to embed"}'

Details

Languages, data & research

Languages

en

Tags

timm pytorch histology pathology vision self-supervised vit image-feature-extraction en

Licence

Commercial licence needed

The weights are open but cc-by-nc-nd-4.0 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

Want UNI2-h on EU-owned hardware?

Request a licence + hosting quote See what’s served now

Explore

More embedding models

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