Text Classification
setfit
Safetensors
sentence-transformers
roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use mini1013/master_cate_bc21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use mini1013/master_cate_bc21 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("mini1013/master_cate_bc21") - sentence-transformers
How to use mini1013/master_cate_bc21 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mini1013/master_cate_bc21") 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:
- 3203fe10ac8ed8d0c22808d425505fe81131f5ac1d3d22d0397493a33e0b07aa
- Size of remote file:
- 442 MB
- SHA256:
- fb68a49a4c366fa2fe7de5d71565380760452bc22ae1cf4cd64f95460537b495
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