Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use djsull/setfit_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use djsull/setfit_classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("djsull/setfit_classifier") - sentence-transformers
How to use djsull/setfit_classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("djsull/setfit_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:
- 9d8b38b0b8090b0a015a52e5c02f26e2bf98c6fc68167c065686e411a4944f35
- Size of remote file:
- 1.28 MB
- SHA256:
- 80e4065a19524f6e03e1308b08a0bd8ffbb7835e346b61739b0152a0686b7ccc
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