|
--- |
|
license: openrail |
|
datasets: |
|
- huolongguo10/insecure |
|
language: |
|
- en |
|
library_name: transformers |
|
pipeline_tag: text-classification |
|
tags: |
|
- code |
|
--- |
|
# 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。 |
|
## 类型 |
|
``` |
|
LABEL_0: secure |
|
LABEL_1: insecure(可能包含payload) |
|
``` |
|
|
|
## 使用 |
|
```python |
|
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' |
|
``` |