How to use Starkdoorstep12/entity-resolution-biencoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Starkdoorstep12/entity-resolution-biencoder") sentences = [ "Uptown Pub! | 1589 Clover Lane, Wichita Falls, TX", "Moa LLC Services | 1964 341, VEEDERSBURG, IN", "Wong Peak-(One) | 2658 61, Vincennes, Indiana", "Uptown Pub! Trading | " ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/Starkdoorstep12/entity-resolution-biencoder/resolve/main/3_Normalize/config.json
hf download hf://Starkdoorstep12/entity-resolution-biencoder/3_Normalize/config.json
curl -L -o config.json https://huggingface.co/Starkdoorstep12/entity-resolution-biencoder/resolve/main/3_Normalize/config.json
