Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use snowdere/trainer_topic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use snowdere/trainer_topic with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("snowdere/trainer_topic") - sentence-transformers
How to use snowdere/trainer_topic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("snowdere/trainer_topic") 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:
- 87a9738cd1f84cb136e2dcbb8cee36735aa8eaccda51158d49c9cab78b3dc952
- Size of remote file:
- 328 kB
- SHA256:
- a309db939adaa51b99d56df38bcff14008be433bcd66cc9236f665a71f6a256b
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