Instructions to use math8485/sbert_mc_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use math8485/sbert_mc_classification with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("math8485/sbert_mc_classification") 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] - setfit
How to use math8485/sbert_mc_classification with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("math8485/sbert_mc_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 477ee69e370d71289295e1e38218ad1089350dacb30593caf5abab8bbe8ac9bd
- Size of remote file:
- 438 MB
- SHA256:
- 671f2a55be51d315849990ddb2df12e21ab4434a6bded9c42a81c7735b2c04ea
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