How to use Alexhuou/embedder_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Alexhuou/embedder_model") sentences = [ "Statutes are often called ________ law.", "Calculate spin density on the central carbon atom of malonic acid radical (•CH(COOH)2) if the hyperfine value for the α-hydrogen atom is 21.9 G.", "Which of the following quotations best describes the central thesis of difference feminism?", "If a relevant variable is omitted from a regression equation, the consequences would be that:\n\ni) The standard errors would be biased\n\n\nii) If the excluded variable is uncorrelated with all of the included variables, all of\n\nthe slope coefficients will be inconsistent.\n\n\niii) If the excluded variable is uncorrelated with all of the included variables, the\n\nintercept coefficient will be inconsistent.\n\n\niv) If the excluded variable is uncorrelated with all of the included variables, all of\n\nthe slope and intercept coefficients will be consistent and unbiased but inefficient." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
