How to use tomaarsen/mpnet-base-nq-cgist-triplet-neg-gte with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tomaarsen/mpnet-base-nq-cgist-triplet-neg-gte") sentences = [ "what does the accounts receivable turnover measure?", "The accounts receivable turnover ratio is an accounting measure used to quantify a company's effectiveness in collecting its receivables or money owed by clients. The ratio shows how well a company uses and manages the credit it extends to customers and how quickly that short-term debt is collected or is paid.", "Capital budgeting, and investment appraisal, is the planning process used to determine whether an organization's long term investments such as new machinery, replacement of machinery, new plants, new products, and research development projects are worth the funding of cash through the firm's capitalization structure ( ...", "The accounts receivable turnover ratio is an accounting measure used to quantify a company's effectiveness in collecting its receivables or money owed by clients. The ratio shows how well a company uses and manages the credit it extends to customers and how quickly that short-term debt is collected or is paid." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
