Model reference · open weights
sentence-t5-xl is an open-weight embedding model from sentence-transformers. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | sentence-transformers |
|---|---|
| Type | Embedding models |
| Task | Embeddings |
| Parameters (lead) | 1.2B |
| Context | 512 tokens |
| Runs with | sentence-transformers |
| Released | 2022-03-02 |
| Popularity | 3k downloads / month |
| Licence | Open weights |
About
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 st5-3b-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 T5-3B model. The weights are stored in FP16.
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('sentence-transformers/sentence-t5-xl')
embeddings = model.encode(sentences)
print(embeddings)
The model requires sentence-transformers version 2.2.0 or newer.
If you find this model helpful, please cite the respective publication: Sentence-T5: Scalable sentence encoders from pre-trained text-to-text models
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys sentence-t5-xl for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (sentence-t5-xl 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-xl","input":"text to embed"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.