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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.
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