rntc / mc-bio-gliner-lymphome-joint

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30-day runs: 271
Model's Last Updated: July 22 2026
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Introduction of mc-bio-gliner-lymphome-joint

Model Details of mc-bio-gliner-lymphome-joint

MC-bio-gliner — lymphoma eCRF (joint supervision)

French biomedical structured extractor (GLiNER2 architecture, ~150M parameters) built on the MedEmbed-v9 sentence-embedding backbone. Fine-tuned on a synthetic lymphoma electronic case report form (eCRF) task with 89 fields.

This checkpoint is the one used to produce the reported scores in the thesis chapter Evaluating Open-Vocabulary Extraction (capstone eCRF).

Results (410-document synthetic test split, value-F1 with field competition)
  • value-F1: 0.657 (best generator-free variant; within 0.018 of the best LLM generator, 27x smaller)
Important note on data

The lymphoma eCRF is entirely synthetic ( rntc/lymphome-synth-v4 ), not real hospital data. It imitates a longitudinal clinical study form. See the thesis for the evaluation protocol (validation-selected threshold, test never used for selection).

Usage
from gliner2 import GLiNER2
model = GLiNER2.from_pretrained("rntc/mc-bio-gliner-lymphome-joint")
Variants
  • rntc/mc-bio-gliner-lymphome — simple supervision (value-F1 0.640 / span-F1 0.503)
  • rntc/mc-bio-gliner-lymphome-joint — joint supervision (value-F1 0.657)

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379
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mc-bio-gliner-lymphome-joint install

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