Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use ashercn97/medicalcode-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use ashercn97/medicalcode-classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ashercn97/medicalcode-classifier") - sentence-transformers
How to use ashercn97/medicalcode-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ashercn97/medicalcode-classifier") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5749d1d06adbe99179142b5e590d8449a822437d25cdd1de4bbc9069a753fac1
- Size of remote file:
- 438 MB
- SHA256:
- 9506cf0a989cf5fe5511a45b16d1a04d47af4f443e3ed7e1c1cd9d81de1414ea
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