Update app.py

app.py

@@ -1,34 +1,3 @@
-import torch
 import gradio as gr
-from diffusers import FluxPipeline
-
-# Load FLUX.1-dev model
-pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
-pipe.enable_model_cpu_offload()  # Saves VRAM by offloading to CPU if needed
-
-def generate_image(prompt):
-    """Generates an image based on user input"""
-    image = pipe(
-        prompt,
-        height=1024,
-        width=1024,
-        guidance_scale=3.5,
-        num_inference_steps=50,
-        max_sequence_length=512,
-        generator=torch.Generator("cpu").manual_seed(0)
-    ).images[0]
-    
-    return image
-
-# Create Gradio interface
-demo = gr.Interface(
-    fn=generate_image,
-    inputs=gr.Textbox(label="Enter your prompt"),
-    outputs=gr.Image(label="Generated Image"),
-    title="FLUX Image Generator",
-    description="Enter a text prompt and generate an image using FLUX.1-dev"
-)
-
-if __name__ == "__main__":
-    demo.launch()
 
+gr.load("models/black-forest-labs/FLUX.1-dev").launch()