Update app.py

app.py

@@ -1,6 +1,6 @@
 from transformers import pipeline
 import gradio as gr
-
+import spaces
 # Initialize the text generation pipeline with optimizations
 pipe = pipeline("text-generation", model="SakanaAI/EvoLLM-JP-v1-7B")
 # Define a function to generate text based on user input
@@ -8,12 +8,18 @@ def generate_text(prompt):
     result = pipe(prompt, max_length=50, num_return_sequences=1)
     return result[0]['generated_text']
 
+# Define a function to generate text based on user input
+@spaces.GPU
+def generate_text(prompt):
+    result = pipe(prompt, max_length=50, num_return_sequences=1)
+    return result[0]['generated_text']
+
 # Create a Gradio interface with batching enabled
 iface = gr.Interface(
     fn=generate_text, 
     inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."), 
     outputs="text",
-    title="Text Generation with DiscoPOP-zephyr-7b-gemma",
+    title="Text Generation with SakanaAI/EvoLLM-JP-v1-7B",
     description="Enter a prompt and the model will generate a continuation of the text.",
     batch=True,
     max_batch_size=4