app.py

app.py

@@ -0,0 +1,24 @@
+
+import gradio as gr
+from transformers import pipeline, BertForSequenceClassification, BertTokenizer
+
+# Load the model and tokenizer from the Hugging Face Hub
+model = BertForSequenceClassification.from_pretrained("Ai_text_model")
+tokenizer = BertTokenizer.from_pretrained("Ai_text_model")
+
+# Create a pipeline
+text_classification = pipeline('text-classification', model=model, tokenizer=tokenizer)
+
+# Define the Gradio interface function
+def classify_text(text):
+    result = text_classification(text)
+    label = result[0]['label']
+    return label
+
+# Create Gradio interface
+interface = gr.Interface(fn=classify_text, inputs='text', outputs='text', title='Text Classification', description='Classify text as human or AI generated')
+
+if __name__ == "__main__":
+    interface.launch()
+
+