How to use pawan2411/semantic-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pawan2411/semantic-embedding") sentences = [ "show my holdings that have performed well over the past 10 years", "Do I hold any premium investment options?", "Show me the investments that have generated the highest returns over the past 10 years", "What implications does this news have for my portfolio's income generation?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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