How to use gubartz/facet_retriever with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gubartz/facet_retriever") sentences = [ "method: Making reflective work practices visible", "method: Job quality takes into account both wage and non-wage attributes of a job.", "purpose: There could therefore be rank differences in the leadership behavioural patterns of managers.", "negative: SN has a positive effect on the user's intention to use toward the SNS." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/gubartz/facet_retriever/resolve/main/tokenizer.json
hf download hf://gubartz/facet_retriever/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/gubartz/facet_retriever/resolve/main/tokenizer.json
