test gradio

app.py

@@ -15,9 +15,9 @@ import os
 token = os.getenv("HF_TOKEN")
 login(token=token)
 
-# Model and ControlNet IDs
-model_id = "runwayml/stable-diffusion-v1-5"  # Known compatible model with ControlNet
-controlnet_id = "lllyasviel/sd-controlnet-canny"  # ControlNet model for edge detection
+# Model IDs for the base Stable Diffusion model and ControlNet variant
+model_id = "stabilityai/stable-diffusion-3.5-large-turbo"
+controlnet_id = "lllyasviel/control_v11p_sd15_inpaint"  # Make sure this ControlNet is compatible
 
 # Load ControlNet model and other components
 controlnet = ControlNetModel.from_pretrained(controlnet_id, torch_dtype=torch.float16)
@@ -26,9 +26,7 @@ pipeline = StableDiffusionControlNetPipeline.from_pretrained(
     controlnet=controlnet,
     torch_dtype=torch.float16
 )
-
-# Optional: Set up the faster scheduler
-pipeline.scheduler = UniPCMultistepScheduler.from_config(pipeline.scheduler.config)
+pipeline = pipeline.to("cuda") if torch.cuda.is_available() else pipeline
 
 # Enable CPU offloading for memory optimization
 pipeline.enable_model_cpu_offload()