Create app.py

app.py

@@ -0,0 +1,22 @@
+import gradio as gr
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+# Load the pre-trained model and tokenizer
+model_name = "microsoft/DialoGPT-small"
+model = GPT2LMHeadModel.from_pretrained(model_name)
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+
+def generate_response(prompt, max_length=50, temperature=0.8):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+    output_ids = model.generate(input_ids, max_length=max_length, temperature=temperature, num_return_sequences=1)
+    response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    return response
+
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(),
+    outputs="text",
+    capture_session=True
+)
+
+iface.launch()