app.py

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()