Create app.py

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+from transformers import pipeline, set_seed
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+set_seed(42)
+num_labels=2
+id2label = {0:'benign',1:'phishing'}
+label2id = {'benign':0,'phishing':1}
+checkpoint = 'bgspaditya/distilbert-phish'
+tokenizer = AutoTokenizer.from_pretrained(checkpoint, use_fast=True, force_download=True)
+model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=num_labels, id2label=id2label, label2id=label2id, force_download=True)
+
+def predict(url):
+    url_classifier = pipeline(task='text-classification', model=model, tokenizer=tokenizer)
+    result = url_classifier(url)
+    return {'label': result[0]['label'], 'score': result[0]['score']}
+
+gradio_app = gr.Interface(
+    predict,
+    inputs=gr.Textbox(label="Enter URL"),
+    outputs=gr.Label(label="Result"),
+    title="Phishing URL Detection",
+)
+
+if __name__ == "__main__":
+    gradio_app.launch()