How to use RohitUltimate/Qwen3-0.6B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RohitUltimate/Qwen3-0.6B") sentences = [ " gbp issued by the surrey oaks surrey june james connolly transaction card", "Food and subsistence", "Other direct costs", "Directors' current accounts" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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