Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Dangurangu/setfit-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Dangurangu/setfit-model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Dangurangu/setfit-model") - sentence-transformers
How to use Dangurangu/setfit-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Dangurangu/setfit-model") 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:
- 0a46e121ceacebfb2a8cc0d364b06c5920f9a2493d8d99cccfbe761077cf8653
- Size of remote file:
- 438 MB
- SHA256:
- ab3da91d2b4a9475d50c8fa984783f422b31542868e48209961206c3caf8caca
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