Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use tstadel/answer-classification-setfit-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use tstadel/answer-classification-setfit-v2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("tstadel/answer-classification-setfit-v2") - sentence-transformers
How to use tstadel/answer-classification-setfit-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tstadel/answer-classification-setfit-v2") 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:
- ea6b98746d3ead711321e5c8961be0e4b9e557d6344fa92995b79e968a443c60
- Size of remote file:
- 25.5 kB
- SHA256:
- 02216f48bb44a8207f906dcfd3e4d069fd9a8748b42cafa4bde07feaff554966
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