| import torch | |
| import gradio as gr | |
| from typing import Dict | |
| from transformers import pipeline | |
| def phishing_not_phishing_classifier(text:str) -> Dict[str, float]: | |
| phishing_not_phishing_classifier_pipeline = pipeline(task="text-classification", | |
| model="twoweeksgetheart/learn_hf_phishing_not_phishing_text_classifier", | |
| batch_size=32, | |
| device="cuda" if torch.cuda.is_available() else "cpu", | |
| top_k=None) | |
| outputs = phishing_not_phishing_classifier_pipeline(text)[0] | |
| outpid_dict = {} | |
| for item in outputs: | |
| outpid_dict[item["label"]] = item["score"] | |
| return outpid_dict | |
| description = """ | |
| Является ли сообщение фишингом или нет | |
| """ | |
| demo = gr.Interface( | |
| fn=phishing_not_phishing_classifier, | |
| inputs="text", | |
| outputs=gr.Label(num_top_classes=2), | |
| title="Классификация фишинговых сообщений", | |
| description=description, | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |