How to use vineet10/fm1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vineet10/fm1") sentences = [ "Users are entitled to a refund for excess payments after necessary deductions, provided that payments were not processed to a wrong account due to user error.", "What is the timeline for the delivery of the documentary film as outlined in this contract?", "Under what circumstances can a user receive a refund for multiple payments made for a single order?", "What are the Payment Terms for the Batteries?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/vineet10/fm1/resolve/main/sentence_bert_config.json
hf download hf://vineet10/fm1/sentence_bert_config.json
curl -L -o sentence_bert_config.json https://huggingface.co/vineet10/fm1/resolve/main/sentence_bert_config.json
