Upload app.py with huggingface_hub

app.py

@@ -0,0 +1,42 @@
+import gradio as gr
+from transformers import pipeline
+import torch
+import spaces
+
+# Load the model pipeline
+pipe = pipeline("text-generation", model="google/vaultgemma-1b", device="cuda", torch_dtype=torch.float16)
+
+# Define the chat function
+@spaces.GPU(duration=120)
+def chat(message, history):
+    # Format the conversation history for the model
+    prompt = ""
+    for user_msg, bot_msg in history:
+        prompt += f"User: {user_msg}\nAssistant: {bot_msg}\n"
+    prompt += f"User: {message}\nAssistant:"
+    
+    # Generate response
+    response = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_p=0.9)
+    generated_text = response[0]['generated_text']
+    
+    # Extract only the assistant's response
+    assistant_response = generated_text.split("Assistant:")[-1].strip()
+    
+    return assistant_response
+
+# Create the Gradio chat interface
+demo = gr.ChatInterface(
+    fn=chat,
+    title="VaultGemma-1B Chatbot",
+    description="A chatbot powered by Google's VaultGemma-1B model.",
+    theme="soft",
+    examples=[
+        "What is the capital of France?",
+        "Tell me a joke.",
+        "Explain quantum computing in simple terms."
+    ],
+    concurrency_limit=1
+)
+
+# Launch the app
+demo.launch()