Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load a pre-trained sentiment-analysis model
+classifier = pipeline('ChavinloSocialRise/bot_rejection_model')
+
+# Define a function to classify the input text
+def classify_text(text):
+    result = classifier(text)[0]  # Get the first result
+    label = result['label']       # The label (e.g., POSITIVE, NEGATIVE)
+    score = result['score']       # The confidence score
+    return f"Label: {label}, Confidence: {score:.4f}"
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=classify_text,  # Function to call
+    inputs="text",     # Input: a text box
+    outputs="text",    # Output: text
+    title="Text Classifier",
+    description="Enter some text and see the classification result."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()