sentence-transformers How to use qcsun/financial-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("qcsun/financial-embedding")
sentences = [
"PACER FDS TR SWAN SOS FLEX JULY ETF(PSFJ)周线级别突破关键阻力位，技术面呈现强势",
"市场解读行业政策对NUVL的积极影响",
"PACER FDS TR SWAN SOS FLEX JULY ETF(PSFJ)技术指标发出看涨信号，短期或延续涨势",
"FTXR"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
