How to use yenstdi/embbedding_text_1111 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yenstdi/embbedding_text_1111") sentences = [ "定期定額投資的優缺點", "近年來大型語言模型與擴散模型在圖像與文本生成領域取得突破性進展。", "國際間的生產與物流體系正在發生重大的組織變革與調整。", "透過固定金額長期投入，投資者能有效攤平市場波動帶來的成本風險，但可能在強勁牛市中錯失更高的單筆申購報酬。" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
