Model reference · open weights
UMLSBert_ENG is an open-weight embedding model from GanjinZero. 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 | GanjinZero |
|---|---|
| Type | Embedding models |
| Task | Embeddings |
| Parameters (lead) | 109M |
| Context | 512 tokens |
| Runs with | transformers |
| Released | 2022-03-02 |
| Popularity | 1k downloads / month |
| Licence | Open weights |
About
CODER: Knowledge infused cross-lingual medical term embedding for term normalization. English Version. Old name. This model is not UMLSBert!!!
Github Link: https://github.com/GanjinZero/CODER
@article{YUAN2022103983,
title = {CODER: Knowledge-infused cross-lingual medical term embedding for term normalization},
journal = {Journal of Biomedical Informatics},
pages = {103983},
year = {2022},
issn = {1532-0464},
doi = {https://doi.org/10.1016/j.jbi.2021.103983},
url = {https://www.sciencedirect.com/science/article/pii/S1532046421003129},
author = {Zheng Yuan and Zhengyun Zhao and Haixia Sun and Jiao Li and Fei Wang and Sheng Yu},
keywords = {medical term normalization, cross-lingual, medical term representation, knowledge graph embedding, contrastive learning}
}
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys umlsbert-eng for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (umlsbert-eng 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":"umlsbert-eng","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.