Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:828486
loss:SymmetricLoss
text-embeddings-inference
Instructions to use WeihaoLi/full_icd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use WeihaoLi/full_icd with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("WeihaoLi/full_icd") sentences = [ "Infectious and parasitic diseases → Viral infection", "Diseases of the blood and blood-forming organs", "Infectious and parasitic diseases", "Diseases of the nervous system and sense organs → Central nervous system infection" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Upload pairs_onehop.csv
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