How to use mabosaimi/bge-m3-text2tables with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mabosaimi/bge-m3-text2tables") sentences = [ "Show the distribution of order values in bands", "Table: orders — Sales orders placed by customers; header level details.", "Table: crm_interactions — Logged emails, calls, and meetings with leads or customers.", "Table: leads — Prospective customers captured by marketing or sales." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
