How to use PhilipCisco/qwen3-base-financial_3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PhilipCisco/qwen3-base-financial_3") sentences = [ "What was the cash dividend per common share declared by Comcast in 2023?", "Pursuant to laws and regulations that include the Federal Food, Drug, and Cosmetic Act (FDCA), the FDA has jurisdiction over all of our products and devices in the U.S. and administers requirements covering the testing, safety, effectiveness, manufacturing, quality control, distribution, labeling, marketing, promotion, advertising, dissemination of information, and post-marketing surveillance of those products and devices.", "Our inventory balance as of January 28, 2024 was $1.3 billion, a decrease of 9% from January 29, 2023.", "Cash dividends declared per common share were $1.16 in 2023." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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