Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use NLBSE/nlbse25_java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use NLBSE/nlbse25_java with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("NLBSE/nlbse25_java") - sentence-transformers
How to use NLBSE/nlbse25_java with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NLBSE/nlbse25_java") 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
File size: 201 Bytes
bce76ea | 1 2 3 4 5 6 7 8 9 10 | {
"__version__": {
"sentence_transformers": "3.1.1",
"transformers": "4.44.2",
"pytorch": "2.4.1+cu121"
},
"prompts": {},
"default_prompt_name": null,
"similarity_fn_name": null
} |