How to use noystl/recomb-pred-all-mpnet-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("noystl/recomb-pred-all-mpnet-base") sentences = [ "Background: The study addresses the need for effective tools that allow both novice and expert users to analyze the diversity of news coverage about events. It highlights the importance of tailoring the interface to accommodate non-expert users while also considering the insights of journalism-savvy users, indicating a gap in existing systems that cater to varying levels of expertise in news analysis.\nContribution: Combine 'a coordinated visualization interface tailored for visualization non-expert users' and ", "a method considering lexical relationships", "cross-modality self-supervised learning via masked visual language modeling", "cognitive models of chaining" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
nielsr