How to use belta1/bc_pibot_intent_setfit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("belta1/bc_pibot_intent_setfit") 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/belta1/bc_pibot_intent_setfit/resolve/main/encoder/tokenizer.json
hf download hf://belta1/bc_pibot_intent_setfit/encoder/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/belta1/bc_pibot_intent_setfit/resolve/main/encoder/tokenizer.json
