huolongguo10/insecure
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How to use huolongguo10/check_sec with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="huolongguo10/check_sec") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("huolongguo10/check_sec")
model = AutoModelForSequenceClassification.from_pretrained("huolongguo10/check_sec")检查web参数安全性,支持多种payload(v0.1.2) 注意:该版本不再维护,请使用tiny版。
LABEL_0: secure
LABEL_1: insecure(可能包含payload)
import transformers
from transformers import BertTokenizer, DataCollatorWithPadding
from transformers import AutoModelForSequenceClassification
tokenizer = BertTokenizer.from_pretrained('huolongguo10/check_sec_tiny')
model = AutoModelForSequenceClassification.from_pretrained('huolongguo10/check_sec_tiny', num_labels=2)
import torch
def check(text):
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
logits = model(**inputs).logits
predicted_class_id = logits.argmax().item()
print(f'{logits.argmax().item()}:{text}')
return 'secure' if predicted_class_id==0 else 'insecure'