Feature Extraction
Transformers
Safetensors
English
bert
medical
clinical
sapbert
biomedical
snomed-ct
loinc
rxnorm
omop
metric-learning
entity-linking
cross-encoder
graph-rag
knowledge-graph
text-embeddings-inference
Instructions to use gitmodelmujtaba/sapbert-snomed-loinc-rxnorm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gitmodelmujtaba/sapbert-snomed-loinc-rxnorm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="gitmodelmujtaba/sapbert-snomed-loinc-rxnorm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gitmodelmujtaba/sapbert-snomed-loinc-rxnorm") model = AutoModel.from_pretrained("gitmodelmujtaba/sapbert-snomed-loinc-rxnorm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
18 days ago
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Update model card: Contrastive adapter, 1,843 concept overrides, and 2.24M-edge Graph-RAG engine
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Update model card: Contrastive adapter, 1,843 concept overrides, and 2.24M-edge Graph-RAG engine
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26 days ago
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docs: set v1.0 as default version, add clinical examples & Colab/Kaggle starter code
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Update documentation with SOTA Dual-Pass 0.4427 Macro-IoU and Active Learning
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Update Model Card with RUN-008 benchmarks, ECE calibration (3.87%), Span IoU precision, and usage guides
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Update Model Card with RUN-008 benchmarks, ECE calibration (3.87%), Span IoU precision, and usage guides
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Update Model Card with RUN-008 benchmarks, ECE calibration (3.87%), Span IoU precision, and usage guides
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Publish RUN-008 Full-Scale Cross-Encoder Benchmarks and Strategic Enhancements
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Deploy Full-Scale Stage-2 Cross-Encoder (Val Acc 96.83%, Strict R@1 33.44%)
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weights: upload supervised Stage-2 Cross-Encoder checkpoint (Val Acc 82.5%)
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weights: update tokenizer.json with domain-adapted checkpoint
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weights: update model.safetensors with domain-adapted checkpoint
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docs: update model card with full-scale 75,490 benchmark results and tri-vocab support
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Initial release of SapBERT trained on SNOMED CT, LOINC, and RxNorm
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initial commit
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