How to use IshTale/MultiEccomerceEmbeddingModel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("IshTale/MultiEccomerceEmbeddingModel") sentences = [ "motion-activated security light with adjustable settings", "LED Black Motion Sensor 2-Light Bullet Flood Light- 3000K Adjustable Dual Head Outdoor Security Light, Dusk to Dawn, Waterproof, Hardwired Spotlight for Yard, Patio, Garage, Landscape", "Waterpik Cordless Advanced Water Flosser", "Tabi Ballet Flats Shoes for Women Rounde Toe Wide Width Split Toe Low Heel Comfortable Flats Shoes" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
