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Update README.md

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@@ -68,7 +68,7 @@ The model's performance is dependent on the nature and quality of the training d
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  ### Transformers
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  ```python
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- from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  import torch
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  tokenizer = AutoTokenizer.from_pretrained("laiyer/deberta-v3-base-prompt-injection")
@@ -80,7 +80,7 @@ classifier = pipeline(
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  tokenizer=tokenizer,
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  truncation=True,
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  max_length=512,
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- device=torch.device("cuda" if torch.cuda.is_available() else "CPU"),
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  )
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  print(classifier("Your prompt injection is here"))
 
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  ### Transformers
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  ```python
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+ from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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  import torch
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  tokenizer = AutoTokenizer.from_pretrained("laiyer/deberta-v3-base-prompt-injection")
 
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  tokenizer=tokenizer,
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  truncation=True,
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  max_length=512,
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+ device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
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  )
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  print(classifier("Your prompt injection is here"))