Text Classification
setfit
Safetensors
sentence-transformers
roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use mini1013/master_cate_fi3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use mini1013/master_cate_fi3 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("mini1013/master_cate_fi3") - sentence-transformers
How to use mini1013/master_cate_fi3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mini1013/master_cate_fi3") 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:
- 90c606987ac4aef4981d8857b04d37cb397026816461ad1dcc33ae9f5b557c1b
- Size of remote file:
- 31.6 kB
- SHA256:
- e4f0d25450e05990a34f66082565435042f7e79ec19a94834d8e06a6670233e0
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