Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use tstadel/answer-classification-setfit-v2-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use tstadel/answer-classification-setfit-v2-binary with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("tstadel/answer-classification-setfit-v2-binary") - sentence-transformers
How to use tstadel/answer-classification-setfit-v2-binary with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tstadel/answer-classification-setfit-v2-binary") 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:
- e2037df0feec52d36f3919ff038c3bc0fd3c6036172e5a8abbd187f684ffc021
- Size of remote file:
- 6.99 kB
- SHA256:
- cdc438ac9e7d71a242df9f9c31253f75914c6f16e3dfccd8d09613c100b69fa4
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