How to use GozdeA/tennis-multi-return-catboost-v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GozdeA/tennis-multi-return-catboost-v3") sentences = [ "2026 for Djokovic?", "What is the serve speed for he?", "momentum for Djokovic?", "2026 for Sinner?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/GozdeA/tennis-multi-return-catboost-v3/resolve/main/tokenizer.json
hf download hf://GozdeA/tennis-multi-return-catboost-v3/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/GozdeA/tennis-multi-return-catboost-v3/resolve/main/tokenizer.json
