Create app.py

app.py

@@ -0,0 +1,22 @@
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+
+# Load your model (replace with your model ID)
+model_id = "yourusername/your-model-name"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+chatbot = pipeline("conversational", model=model, tokenizer=tokenizer)
+
+# Chat function with memory
+def respond(message, history):
+    conversation = []
+    for user_msg, bot_msg in history:
+        conversation.append({"role": "user", "content": user_msg})
+        conversation.append({"role": "assistant", "content": bot_msg})
+    conversation.append({"role": "user", "content": message})
+    
+    response = chatbot(conversation)
+    return response[-1]["generated_text"]
+
+# Launch interface
+gr.ChatInterface(respond).launch()