How to use fabiancpl/nlbse25_python with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("fabiancpl/nlbse25_python") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds)
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]
https://huggingface.co/fabiancpl/nlbse25_python/resolve/main/tokenizer.json
hf download hf://fabiancpl/nlbse25_python/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/fabiancpl/nlbse25_python/resolve/main/tokenizer.json
