add description

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 the results in the online demo are unstable: The same code, weights and random seeds have huge differences in results under different spaces, which may due to the ZeroGPU. If it is convenient, please git clone and run it locally.**"
+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 the results in HF online demo are unstable and worse, which may due to the ZeroGPU. If it is convenient, please git clone and run it locally.**"
 
 if not torch.cuda.is_available():
     DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"