Create app.py

app.py

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+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import gradio as gr
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+model = AutoModelForCausalLM.from_pretrained("gpt2")
+
+
+def generate_response(input_text):
+    input_ids = tokenizer.encode(input_text, return_tensors='pt')
+    generated_output = model.generate(input_ids, max_length=100, num_return_sequences=1)
+    response = tokenizer.decode(generated_output[0], skip_special_tokens=True)
+    return response
+
+
+iface = gr.Interface(
+    fn=generate_response,
+    inputs='text',
+    outputs='text',
+    layout='vertical',
+    title='ChatGPT',
+    description='A simple chatbot powered by ChatGPT',
+    article= 'https://huggingface.co/models',
+    examples=[['Hello'], ['How are you?'], ['What is your name?']],
+)
+
+iface.launch()