How to use davanstrien/headline-similarity with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("davanstrien/headline-similarity") sentences = [ "WOMEN MARCH ON SEN. HARDING NATIONAL WOMEN'S PARTY WANTS SENATOR'S AID IN TENNESSEE SUFF FIGHT", "WOMEN T0 MARCH ON SEN. HARDING", "SERVICE DEPARTMENT WITHOUT ASSISTANT!", "FEDERAL AGENTS WILL ARREST ' DEALERS WHO CHARGE TOO MUCH, SAYS DEPARTMENT OF JUSTICE." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
How to use davanstrien/headline-similarity with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("davanstrien/headline-similarity") model = AutoModel.from_pretrained("davanstrien/headline-similarity")