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8ddf1bc
1 Parent(s): 8da2e91

Update app.py

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Files changed (1) hide show
  1. app.py +12 -4
app.py CHANGED
@@ -4,15 +4,16 @@ from sentence_transformers import SentenceTransformer
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  texts1 = ["胡子长得太快怎么办?", "在香港哪里买手表好"]
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  texts2 = ["胡子长得快怎么办?", "怎样使胡子不浓密!", "香港买手表哪里好", "在杭州手机到哪里买"]
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  model = SentenceTransformer('DMetaSoul/Dmeta-embedding')
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  embs1 = model.encode(texts1, normalize_embeddings=True)
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  embs2 = model.encode(texts2, normalize_embeddings=True)
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  similarity = embs1 @ embs2.T
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- print(type(embs1), embs1)
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- print(type(embs2), embs2)
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- print(similarity)
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  for i in range(len(texts1)):
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  scores = []
@@ -21,8 +22,15 @@ for i in range(len(texts1)):
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  scores = sorted(scores, key=lambda x:x[1], reverse=True)
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  print(f"查询文本:{texts1[i]}")
 
 
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  for text2, score in scores:
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  print(f"相似文本:{text2},打分:{score}")
 
 
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  print()
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- gr.load("models/DMetaSoul/Dmeta-embedding-zh").launch()
 
 
 
 
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  texts1 = ["胡子长得太快怎么办?", "在香港哪里买手表好"]
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  texts2 = ["胡子长得快怎么办?", "怎样使胡子不浓密!", "香港买手表哪里好", "在杭州手机到哪里买"]
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+ demo_text = ""
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+
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  model = SentenceTransformer('DMetaSoul/Dmeta-embedding')
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  embs1 = model.encode(texts1, normalize_embeddings=True)
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  embs2 = model.encode(texts2, normalize_embeddings=True)
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  similarity = embs1 @ embs2.T
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+ demo_text += similarity
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+ demo_text += "\n"
 
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  for i in range(len(texts1)):
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  scores = []
 
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  scores = sorted(scores, key=lambda x:x[1], reverse=True)
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  print(f"查询文本:{texts1[i]}")
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+ demo_text += f"查询文本:{texts1[i]}"
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+ demo_text += "\n"
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  for text2, score in scores:
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  print(f"相似文本:{text2},打分:{score}")
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+ demo_text += f"相似文本:{text2},打分:{score}"
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+ demo_text += "\n"
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  print()
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+ # gr.load("models/DMetaSoul/Dmeta-embedding-zh").launch()
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+ with gr.Row():
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+ gr.Markdown(demo_text)
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+