Update app.py

app.py

@@ -18,16 +18,16 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 base_model_id = "runwayml/stable-diffusion-v1-5"
 model_id = "LuyangZ/FloorAI"
 
-controlnet = ControlNetModel.from_pretrained(model_id, torch_dtype=torch.float16)
+# controlnet = ControlNetModel.from_pretrained(model_id, torch_dtype=torch.float16)
 # controlnet = ControlNetModel.from_pretrained(model_id, torch_dtype="auto")
-# controlnet = ControlNetModel.from_pretrained(model_id, torch_dtype=torch.float32)
+controlnet = ControlNetModel.from_pretrained(model_id, torch_dtype=torch.float32)
 controlnet.to(device)
 # torch.cuda.empty_cache()
 
 
-# pipeline = StableDiffusionControlNetPipeline.from_pretrained(base_model_id , controlnet=controlnet, torch_dtype=torch.float32)
+pipeline = StableDiffusionControlNetPipeline.from_pretrained(base_model_id , controlnet=controlnet, torch_dtype=torch.float32)
 # pipeline = StableDiffusionControlNetPipeline.from_pretrained(base_model_id , controlnet=controlnet, torch_dtype="auto")
-pipeline = StableDiffusionControlNetPipeline.from_pretrained(base_model_id , controlnet=controlnet, torch_dtype=torch.float16)
+# pipeline = StableDiffusionControlNetPipeline.from_pretrained(base_model_id , controlnet=controlnet, torch_dtype=torch.float16)
 pipeline.scheduler = UniPCMultistepScheduler.from_config(pipeline.scheduler.config)
 
 pipeline = pipeline.to(device)