Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use bew/setfit-subject-model-basic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use bew/setfit-subject-model-basic with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("bew/setfit-subject-model-basic") - sentence-transformers
How to use bew/setfit-subject-model-basic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bew/setfit-subject-model-basic") 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:
- 1271e91f73c755cd55ed95d78e02a864d67abb14193bcf2e7b87d261263ce538
- Size of remote file:
- 133 MB
- SHA256:
- 70e7ceb3c783d84186da0b847beb5192d78bc274b2ede2ef5ea62c4b661216ed
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