Create app.py

app.py

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+# Install dependencies if not already installed
+# !pip install transformers gradio
+
+from transformers import pipeline
+import gradio as gr
+
+# Load your model and tokenizer from Hugging Face
+model_name = "duclo90/Semeval"  # replace with your HF repo
+
+classifier = pipeline(
+    "text-classification",
+    model=model_name,
+    tokenizer=model_name
+)
+
+# Function to classify text
+def classify_text(text):
+    result = classifier(text)
+    label = result[0]['label']
+    score = round(result[0]['score'], 3)
+    return f"Prediction: {label} (Confidence: {score})"
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.Textbox(lines=5, placeholder="Enter text here..."),
+    outputs="text",
+    title="Human vs Machine Text Classifier",
+    description="Enter text and the model will predict if it was written by a human or generated by a machine."
+)
+
+# Launch the web app
+iface.launch(share=True)  # share=True generates a public link