Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use stephen-solka/feed-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use stephen-solka/feed-classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("stephen-solka/feed-classifier") - sentence-transformers
How to use stephen-solka/feed-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("stephen-solka/feed-classifier") 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:
- 4346ae4ac255f0f74b6b267dc51e40ca1becc5857b144b7c74560377d2965dcd
- Size of remote file:
- 1.47 kB
- SHA256:
- 49966b9c9485c189d355d02077cb3f6a0643b3663ab3a1707b08365bdcedb66b
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