How to use moshew/gist_small_ft_gooaq_v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("moshew/gist_small_ft_gooaq_v3") sentences = [ "do vivid seats tickets work?", "Charlotte-Mecklenburg Schools will be closed for students on Friday due to the forecast of severe weather. ... CMS staff members work with city and county leaders to receive the most up-to-date information about road and weather conditions.", "Tickets are $40 per ticket and $400 for a table of ten. Tickets are available for purchase when you register for the show.", "This service is currently offered free of charge by the bank. You can get the last 'Available' balance of your account (by an SMS) by giving a Missed Call to 18008431122. You can get the Mini Statement (by an SMS) for last 5 transactions in your account by giving a Missed Call to 18008431133. 1." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/moshew/gist_small_ft_gooaq_v3/resolve/main/tokenizer.json
hf download hf://moshew/gist_small_ft_gooaq_v3/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/moshew/gist_small_ft_gooaq_v3/resolve/main/tokenizer.json
