How to use MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk") sentences = [ "If you receive a BharatPe speaker that you didn't order, please contact BharatPe support immediately. They will assist in resolving the issue and advise on the next steps.", "Can I control multiple BharatPe speakers from one app?", "What to do if the BharatPe speaker's transaction announcements are intermittently silent?", "What should I do if I receive a BharatPe speaker without ordering it?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk/resolve/main/tokenizer.json
hf download hf://MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/MANMEET75/pubmedbert-base-embedding-Chatbot-Matryoshk/resolve/main/tokenizer.json
