How to use dbourget/pb-ds1-48K-philsim with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dbourget/pb-ds1-48K-philsim") sentences = [ "In The Law of Civilization and Decay, Brooks provides a detailed look at the rise and fall of civilizations, offering a critical perspective on the impact of capitalism. As societies become prosperous, their pursuit of wealth ultimately leads to their own downfall as greed takes over.", "Patrick Todd's The Open Future argues that all future contingent statements, such as 'It will rain tomorrow', are inherently false.", "If propositions are made true in virtue of corresponding to facts, then what are the truth-makers of true negative propositions such as ‘The apple is not red’? Russell argued that there must be negative facts to account for what makes true negative propositions true and false positive propositions false. Others, more parsimonious in their ontological commitments, have attempted to avoid them. Wittgenstein rejected them since he was loath to think that the sign for negation referred to a negative element in a fact. A contemporary of Russell’s, Raphael Demos, attempted to eliminate them by appealing to ‘incompatibility’ facts. More recently, Armstrong has appealed to the totality of positive facts as the ground of the truth of true negative propositions. Oaklander and Miracchi have suggested that the absence or non-existence of the positive fact (which is not itself a further fact) is the basis of a positive proposition being false and therefore of the truth of its negation.", "The Law of Civilization and Decay is an overview of history, articulating Brooks' critical view of capitalism. A civilization grows wealthy, and then its wealth causes it to crumble upon itself due to greed." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
