Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Maxim01/Intent_Classification_Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Maxim01/Intent_Classification_Test with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Maxim01/Intent_Classification_Test") - sentence-transformers
How to use Maxim01/Intent_Classification_Test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Maxim01/Intent_Classification_Test") 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:
- c1b0d6f4f50d2b08ab8d2c81c255794a1db1b1b0394d290b8bd686a78d0e910d
- Size of remote file:
- 471 MB
- SHA256:
- 5907423a9906f5255b78828184b6eafc33d4b5a003620ec1aa2b6938f8321939
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