Create Main.py

Main.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the DialoGPT-medium model and tokenizer (renamed to 1111)
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
+
+# Function for generating responses (renamed as 1111)
+def chat_with_1111(input_text):
+    # Encode the input text using the tokenizer
+    input_ids = tokenizer.encode(input_text + tokenizer.eos_token, return_tensors='pt')
+
+    # Generate a response using the model (1111)
+    chat_history_ids = model.generate(input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
+
+    # Decode and return the response
+    response = tokenizer.decode(chat_history_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
+    return response
+
+# Define the Gradio interface
+iface = gr.Interface(fn=chat_with_1111,
+                     inputs=gr.Textbox(lines=2, placeholder="Ask 1111 a question..."),
+                     outputs="text",
+                     live=True,
+                     title="Chat with 1111",
+                     description="Talk to 1111, an AI trained with DialoGPT medium!")
+
+# Launch the interface (This will run on Aifaces when uploaded)
+iface.launch()