Model reference · open weights

sentence-t5

sentence-t5 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.

Embeddings sentence-transformers 1 variants 155k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What sentence-t5 is

sentence-transformers/sentence-t5-base This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space. The model works well for sentence similarity tasks, but doesn't perform that well for semantic search tasks. This model was converted from the Tensorflow model st5-base-1 to PyTorch. When using this model, have a look at the publication: Sentence-T5: Scalable sentence encoders from pre-trained text-to-text models. The tfhub model and this PyTorch model can produce slightly different embeddings, however, when run on the same benchmarks, they produce identical results. The model uses only the encoder from a T5-base model. The weights are stored in FP16. Usage (Sentence-Transformers) Using this model becomes easy when you have sentence-transformers installed: Then you can use the model like this: The model requires sentence-transformers version 2.2.0 or newer. Citing & Authors If you find this model helpful, please cite the respective publication: Sentence-T5: Scalable sentence encoders from pre-trained text-to-text models

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)110M
Context512 tokens
Variants1
Runs withsentence-transformers
Released2022-03-02
Popularity155k downloads / month
Likes51
LicenceOpen weights

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
sentence-t5-base110MBF16~0.3 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys sentence-t5 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (sentence-t5 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":"sentence-t5","input":"text to embed"}'

Details

Languages, data & research

Languages

en

Tags

sentence-transformers pytorch rust safetensors t5 feature-extraction sentence-similarity en endpoints_compatible

Papers

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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