How to use seregadgl/splade_gemma_google_base_checkpoint_100_ver2_checkpoint100 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("seregadgl/splade_gemma_google_base_checkpoint_100_ver2_checkpoint100") sentences = [ "query: 6460338 acdelco", "document: очиститель тормозов rsqprofessional арт 072589767pl volkswagen id buzz янтарный", "document: гтц 6460338 для chevrolet traverse", "document: гтц 6960358 для chevrolet traverse" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
