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README.md
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## Usage
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```python
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from transformers import AutoTokenizer,
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import torch
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import numpy as np
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model_dir = "kfkas/RoBERTa-large-Detection-P2G"
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tokenizer = AutoTokenizer.from_pretrained(model_dir)
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model =
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text = "μλ컀 νλμν λνν°λ© νμ°λ¬ μ΄λ¬λ¬ μ΄μμμ₯ μ λ¬Ό"
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with torch.no_grad():
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## Usage
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```python
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from transformers import AutoTokenizer, RobertaForSequenceClassification
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import torch
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import numpy as np
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model_dir = "kfkas/RoBERTa-large-Detection-P2G"
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tokenizer = AutoTokenizer.from_pretrained(model_dir)
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model = RobertaForSequenceClassification.from_pretrained(model_dir)
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text = "μλ컀 νλμν λνν°λ© νμ°λ¬ μ΄λ¬λ¬ μ΄μμμ₯ μ λ¬Ό"
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with torch.no_grad():
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