Text Classification
setfit
Safetensors
sentence-transformers
English
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use fabiancpl/nlbse25_python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use fabiancpl/nlbse25_python with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fabiancpl/nlbse25_python") - sentence-transformers
How to use fabiancpl/nlbse25_python with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fabiancpl/nlbse25_python") 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:
- 0f497029cc02f7faa72e8f489f63245b713bdf158a83492a88e2b6afed4869fd
- Size of remote file:
- 90.9 MB
- SHA256:
- 0629ba13577db241ce5f4a6b0f605aad8ee0ff27d4f65bd76e278f2c977b1f47
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