Text Classification
setfit
Safetensors
sentence-transformers
modernbert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use johnpaulbin/toxicity-setfit-5-large-norm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use johnpaulbin/toxicity-setfit-5-large-norm with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("johnpaulbin/toxicity-setfit-5-large-norm") - sentence-transformers
How to use johnpaulbin/toxicity-setfit-5-large-norm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("johnpaulbin/toxicity-setfit-5-large-norm") 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:
- 33cd89ff8b53fbb07f89aa282b3d5bd5f5d7de3a2cdeca8540ee80380a8d3c1c
- Size of remote file:
- 34.4 MB
- SHA256:
- 8bd47075711f75a143d1b78e01a41cc65c1c591b00d3cfeffc23db07adce1392
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