Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use olivepol/SetFit_StanceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use olivepol/SetFit_StanceClassification with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("olivepol/SetFit_StanceClassification") - sentence-transformers
How to use olivepol/SetFit_StanceClassification with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("olivepol/SetFit_StanceClassification") 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:
- fe55999f344f20ac8e3ed658c7447e992995a4418a259219a1e576f6565d5544
- Size of remote file:
- 471 MB
- SHA256:
- 716082719dd53832c9164c6e6dfc6374a3243afbc59a2366a7247a193e80d18e
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