Update app.py

app.py

@@ -17,7 +17,7 @@ from settings import ALLOW_CHANGING_BASE_MODEL, DEFAULT_MODEL_ID, SHOW_DUPLICATE
 from transformers.utils.hub import move_cache
 move_cache()
 
-DESCRIPTION = "# [ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback](https://arxiv.org/abs/2404.07987) \n ### The first row in outputs is the input conditions. The second row is the images generated by ControlNet++. The third row is the conditions extracted from our generated images. Please note that we use the SD1.5 and trained on specific public datasets, so the quality of the generated images may not be as good as models such as SDXL-based models, or trained on private datasets. For example, the image quality and resolution in the ADE20K dataset (Segmentation) are often poor \n **We noticed that the HuggingFace online demo had unstable and worse results, possibly caused by ZeroGPU. We strongly recommend running locally, following the instruction on our [Github Repo](https://github.com/liming-ai/ControlNet_Plus_Plus).**"
+DESCRIPTION = "# [ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback](https://arxiv.org/abs/2404.07987) \n ### The first row in outputs is the input conditions. The second row is the images generated by ControlNet++. The third row is the conditions extracted from our generated images. Please note that we use the SD1.5 and trained on specific public datasets, so the quality of the generated images may not be as good as models such as SDXL-based models, or trained on private datasets. For example, the image quality and resolution in the ADE20K dataset (Segmentation) are often poor \n **Due to ZeroGPU updates, the Huggingface demo may not always work. We strongly recommend running locally, following the instruction on our [Github Repo](https://github.com/liming-ai/ControlNet_Plus_Plus).**"
 
 if not torch.cuda.is_available():
     DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"