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:
- f5df0752560961ee01582e8d2bf5acd09a6351ba03013bc2b5d5396065a01ab8
- Size of remote file:
- 117 MB
- SHA256:
- d271a20b8e11544b7421a9d88d8fec1b708e883606980c872708a9f418d5bd18
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