Create app.py

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+model_name = "MennatullahHany/Tunned_Bert"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+def classify(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.softmax(outputs.logits, dim=1)
+        confidence, predicted = torch.max(probs, dim=1)
+
+    label = model.config.id2label[predicted.item()]
+    confidence = float(confidence.item())
+    return {label: confidence}
+
+iface = gr.Interface(
+    fn=classify,
+    inputs=gr.Textbox(lines=5, placeholder="Enter text here..."),
+    outputs=gr.Label(),
+    title="BERT Safety Classifier",
+    description="Enter text to classify as SAFE or DANGER."
+)
+
+iface.launch()