Text Classification
setfit
Safetensors
sentence-transformers
modernbert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use shwet-docket/setfit-paraphrase-mpnet-base-v2-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use shwet-docket/setfit-paraphrase-mpnet-base-v2-sst2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("shwet-docket/setfit-paraphrase-mpnet-base-v2-sst2") - sentence-transformers
How to use shwet-docket/setfit-paraphrase-mpnet-base-v2-sst2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shwet-docket/setfit-paraphrase-mpnet-base-v2-sst2") 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:
- c32a7db56bf155a35afc4b4c3ca43e351af3d0d13a77611a5634f9fcc2feaf91
- Size of remote file:
- 596 MB
- SHA256:
- 9afa8830e56444648055526b26f15fd28b066fd64c121553de63404f9aeb7e20
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