How to use bwang0911/reasoning-bge with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bwang0911/reasoning-bge") sentences = [ "Hey Reddit, what do you do in New York City?", "The second text directly answers the question posed in the first text. It provides personal recommendations for places to eat and things to do in New York City, fulfilling the user's query. The text also offers a specific recommendation for a restaurant, Crif Dogs, and a menu item.", "For example, let's say you're at a section containing 9 tables\n\n 1 2 3\n 4 5 6\n 7 8 9\n\nI'm sitting on the west side of Table 7, there are people at Tables 5 and 6. Someone comes in through the crowd and sits on the east side of table 8, making awkward eye contact while we've got our mouths full.\n\nI always found it extremely uncomfortable... why oh why can't they just sit with their back to me? As far as I'm concerned this is almost as canonical as urinal rules.", "This is my first year living here and I was just wondering if you knew of any awesome places to eat, fun places to go, trees to climb, anything of the sort. I for one would recommend Crif Dogs to anyone who has not been. Go there and get the \"Spicy Redneck,\" you won't regret it." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
