Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use tushifire/setfit-break_task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use tushifire/setfit-break_task with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("tushifire/setfit-break_task") - sentence-transformers
How to use tushifire/setfit-break_task with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tushifire/setfit-break_task") 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:
- 9d1b662af356878ad8c6ce01c6dc8eb85de7cfc8259192ec92441ed8eaa16e67
- Size of remote file:
- 7.06 kB
- SHA256:
- c9fc7779a0c80b1a4c28b460487515413cc8fa1d2891f03b9449a93e01b7c5a7
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