How to use seanfarrell/icd11_ner_model_small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("seanfarrell/icd11_ner_model_small") sentences = [ "vascular disorders of the stomach", "vascular disorders of the stomach, unspecified", "ringworm of the hand", "anogenital herpes" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/seanfarrell/icd11_ner_model_small/resolve/main/1_Pooling/config.json
hf download hf://seanfarrell/icd11_ner_model_small/1_Pooling/config.json
curl -L -o config.json https://huggingface.co/seanfarrell/icd11_ner_model_small/resolve/main/1_Pooling/config.json
