Upload app.py

app.py

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+import transformers
+import gradio as gr
+import torch
+
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+tokenizer = GPT2Tokenizer.from_pretrained('microsoft/DialoGPT-small')
+model = GPT2LMHeadModel.from_pretrained('microsoft/DialoGPT-small')
+
+def chat(message, token_response):
+    token_message = tokenizer.encode(message + tokenizer.eos_token, return_tensors='pt')
+    token_response = model.generate(token_message, max_length=1000, pad_token_id=tokenizer.eos_token_id)
+    response = tokenizer.decode(token_response[:, token_message.shape[-1]:][0], skip_special_tokens=True)
+    return response, token_response
+
+input = gr.inputs.Textbox(lines=2, label='User:')
+output = gr.outputs.Textbox(label='Bot:')
+
+gr.Interface(fn=chat,
+    title="DialoGPT-small",
+    inputs=[input, "state"],
+    outputs=[output, "state"],
+    allow_screenshot=False,
+    allow_flagging='never').launch()