| --- |
| license: mit |
| base_model: intfloat/multilingual-e5-small |
| library_name: transformers.js |
| tags: [sentence-transformers, feature-extraction, medical, on-device] |
| --- |
| |
| # evum/lab-marker-e5-small |
|
|
| A contrastive fine-tune of [multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) |
| (MIT) for **lab-marker naming** in [Evum](https://github.com/) — it maps a lab-report label |
| (any language) to one of Evum's marker ids by embedding similarity. Runs **on-device** via |
| transformers.js; the user's health data never leaves the browser. |
|
|
| **Open weights, closed recipe:** the weights are public and the eval below is reproducible on |
| the open fixtures, but the training pipeline is proprietary. |
|
|
| ## Eval (held-out fixtures, precision-first) |
| | model | precision | recall | threshold | margin | |
| |---|---|---|---|---| |
| | base multilingual-e5-small | 1.0 | 0.833 | 0.89 | 0.02 | |
| | **this model (q8 ONNX)** | 1.0 | 1.0 | 0.7 | 0 | |
|
|
| ## Use |
| Feature-extraction; prefix report labels with `query: ` and marker names with `passage: `, |
| mean-pool, L2-normalize, cosine similarity. Names only — it never produces a measurement value. |
|
|
| ## Limitations |
| Small fine-tune; a naming *fallback* behind a deterministic catalog. Not medical advice. |
|
|
