Text Classification
setfit
Safetensors
sentence-transformers
new
generated_from_setfit_trainer
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use twright8/news_cats with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use twright8/news_cats with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("twright8/news_cats") - sentence-transformers
How to use twright8/news_cats with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("twright8/news_cats", trust_remote_code=True) 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:
- 402ad7a4d6025e242d076650af06a72f27b6551a55e44227a3890227496d93dc
- Size of remote file:
- 7.7 kB
- SHA256:
- c3f5339885643e3b45e7350dbf556d1f87db4e25888051a738378301c60c8a24
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