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@@ -11,11 +11,11 @@ from transformers import AutoModelForSequenceClassification, AlbertTokenizer
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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- model = AutoModelForSequenceClassification.from_pretrained("axiomlabs/KR-cryptodeberta-v2-base", num_labels=3)
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  model.eval()
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  model.to(device)
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- tokenizer = AlbertTokenizer.from_pretrained("axiomlabs/KR-cryptodeberta-v2-base")
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  title = "우즈벑, μ™Έκ΅­κΈ°μ—…μ˜ μ•”ν˜Έν™”ν 거래자금 κ΅­λ‚΄κ³„μ’Œ μž…κΈˆ ν—ˆμš©"
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  content = "λΉ„νŠΈμ½”μΈλ‹·μ»΄μ— λ”°λ₯΄λ©΄ μš°μ¦ˆλ² ν‚€μŠ€νƒ„ 쀑앙은행이 μ™Έκ΅­κΈ°μ—…μ˜ κ΅­λ‚΄ 은행 κ³„μ’Œ κ°œμ„€ 및 μ•”ν˜Έν™”ν 거래 자금 μž…κΈˆμ„ ν—ˆμš©ν–ˆλ‹€. μ•žμ„œ μš°μ¦ˆλ² ν‚€μŠ€νƒ„μ€ μ™Έκ΅­κΈ°μ—…μ˜ 은행 κ³„μ’Œ κ°œμ„€ 등을 μ œν•œ 및 κΈˆμ§€ν•œ λ°” μžˆλ‹€. κ°œμ •μ•ˆμ— 따라 μ΄λŸ¬ν•œ μžκΈˆμ€ μ•”ν˜Έν™”ν λ§€μž…μ„ μœ„ν•΄ κ±°λž˜μ†Œλ‘œ 이체, ν˜Ήμ€ 자금이 μœ μž…λœ κ΄€ν• κΆŒ λ‚΄ λ“±λ‘λœ 법인 κ³„μ’Œλ‘œ 이체할 수 μžˆλ‹€. λ‹€λ§Œ κ·Έ μ™Έ λ‹€λ₯Έ λͺ©μ μ„ μœ„ν•œ μ‚¬μš©μ€ κΈˆμ§€λœλ‹€. ν•΄λ‹Ή κ°œμ •μ•ˆμ€ μ§€λ‚œ 2μ›” 9일 λ°œνš¨λλ‹€."
@@ -37,11 +37,11 @@ from scipy.spatial.distance import cdist
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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- model = AutoModel.from_pretrained("axiomlabs/KR-cryptodeberta-v2-base")
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  model.eval()
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  model.to(device)
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- tokenizer = AlbertTokenizer.from_pretrained("axiomlabs/KR-cryptodeberta-v2-base")
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  title1 = "USDN 닀쀑담보 μžμ‚° μ „ν™˜ μ œμ•ˆ 톡과"
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  content1 = "μ›¨μ΄λΈŒ μƒνƒœκ³„ μŠ€ν…Œμ΄λΈ”μ½”μΈ USDN을 닀쀑담보 μžμ‚°μœΌλ‘œ μ „ν™˜ν•˜λŠ” μ œμ•ˆ νˆ¬ν‘œκ°€ μ°¬μ„± 99%둜 였늘 톡과됐닀. μ•žμ„œ μ½”μΈλ‹ˆμŠ€λŠ” μ›¨λΈŒκ°€ $WX,$SWOP,$VIRES,$EGG,$WESTλ₯Ό λ‹΄λ³΄λ‘œ ν•΄ USDN을 μ›¨μ΄λΈŒ μƒνƒœκ³„ 인덱슀 μžμ‚°μœΌλ‘œ λ§Œλ“€μ–΄ USDN λ””νŽ˜κΉ… 이슈λ₯Ό ν•΄κ²°ν•  ν”Œλžœμ„ κ³΅κ°œν–ˆλ‹€κ³  μ „ν•œ λ°” μžˆλ‹€."
 
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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+ model = AutoModelForSequenceClassification.from_pretrained("LDKSolutions/KR-cryptodeberta-v2-base", num_labels=3)
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  model.eval()
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  model.to(device)
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+ tokenizer = AlbertTokenizer.from_pretrained("LDKSolutions/KR-cryptodeberta-v2-base")
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  title = "우즈벑, μ™Έκ΅­κΈ°μ—…μ˜ μ•”ν˜Έν™”ν 거래자금 κ΅­λ‚΄κ³„μ’Œ μž…κΈˆ ν—ˆμš©"
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  content = "λΉ„νŠΈμ½”μΈλ‹·μ»΄μ— λ”°λ₯΄λ©΄ μš°μ¦ˆλ² ν‚€μŠ€νƒ„ 쀑앙은행이 μ™Έκ΅­κΈ°μ—…μ˜ κ΅­λ‚΄ 은행 κ³„μ’Œ κ°œμ„€ 및 μ•”ν˜Έν™”ν 거래 자금 μž…κΈˆμ„ ν—ˆμš©ν–ˆλ‹€. μ•žμ„œ μš°μ¦ˆλ² ν‚€μŠ€νƒ„μ€ μ™Έκ΅­κΈ°μ—…μ˜ 은행 κ³„μ’Œ κ°œμ„€ 등을 μ œν•œ 및 κΈˆμ§€ν•œ λ°” μžˆλ‹€. κ°œμ •μ•ˆμ— 따라 μ΄λŸ¬ν•œ μžκΈˆμ€ μ•”ν˜Έν™”ν λ§€μž…μ„ μœ„ν•΄ κ±°λž˜μ†Œλ‘œ 이체, ν˜Ήμ€ 자금이 μœ μž…λœ κ΄€ν• κΆŒ λ‚΄ λ“±λ‘λœ 법인 κ³„μ’Œλ‘œ 이체할 수 μžˆλ‹€. λ‹€λ§Œ κ·Έ μ™Έ λ‹€λ₯Έ λͺ©μ μ„ μœ„ν•œ μ‚¬μš©μ€ κΈˆμ§€λœλ‹€. ν•΄λ‹Ή κ°œμ •μ•ˆμ€ μ§€λ‚œ 2μ›” 9일 λ°œνš¨λλ‹€."
 
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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+ model = AutoModel.from_pretrained("LDKSolutions/KR-cryptodeberta-v2-base")
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  model.eval()
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  model.to(device)
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+ tokenizer = AlbertTokenizer.from_pretrained("LDKSolutions/KR-cryptodeberta-v2-base")
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  title1 = "USDN 닀쀑담보 μžμ‚° μ „ν™˜ μ œμ•ˆ 톡과"
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  content1 = "μ›¨μ΄λΈŒ μƒνƒœκ³„ μŠ€ν…Œμ΄λΈ”μ½”μΈ USDN을 닀쀑담보 μžμ‚°μœΌλ‘œ μ „ν™˜ν•˜λŠ” μ œμ•ˆ νˆ¬ν‘œκ°€ μ°¬μ„± 99%둜 였늘 톡과됐닀. μ•žμ„œ μ½”μΈλ‹ˆμŠ€λŠ” μ›¨λΈŒκ°€ $WX,$SWOP,$VIRES,$EGG,$WESTλ₯Ό λ‹΄λ³΄λ‘œ ν•΄ USDN을 μ›¨μ΄λΈŒ μƒνƒœκ³„ 인덱슀 μžμ‚°μœΌλ‘œ λ§Œλ“€μ–΄ USDN λ””νŽ˜κΉ… 이슈λ₯Ό ν•΄κ²°ν•  ν”Œλžœμ„ κ³΅κ°œν–ˆλ‹€κ³  μ „ν•œ λ°” μžˆλ‹€."