TermMap-X+ (xplus-sf): trained weights

Weights for the TermMap-X+ subconcept-free system (clinical mention + chart chunk -> one ICD-10-CM code and one SNOMED CT concept). Code and instructions: see the GitHub repository's README. Pull with python setup_model.py.

path what base model
models/sapbert-ft/ SapBERT fine-tuned (InfoNCE) on training mentions -> dictionary names cambridgeltl/SapBERT-from-PubMedBERT-fulltext
models/cross-ctx/ X's cross-encoder, mention + chart context, listwise 1+7 microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
models/cross-noctx/ X's cross-encoder, mention only microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
data/processed/dense_*.npy SapBERT-ft embeddings of every dictionary alias (fp16) -

Not included: the char TF-IDF + BM25 alias indexes (data/processed/lexical_*.pkl); termmap rebuilds them from the alias tables on first run. Also not included (public, pulled at pinned revisions by setup_model.py): Qwen/Qwen2.5-1.5B-Instruct (SNOMED gate), Qwen/Qwen3-Reranker-0.6B (ICD zero-shot scorer). Every file is listed with its sha256 in WEIGHTS_MANIFEST.json.

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