Update app.py

app.py

@@ -41,7 +41,7 @@ We then trained four Control-Nets with different mixtures of 2 datasets (Coyo-70
 
 Model Description and Training Process: Please refer to the readme file attached to the model repository.
 
-Model Repository: [ControlNet repo](https://huggingface.co/Baptlem/baptlem-controlnet)
+Model Repository: [ControlNet repo](https://huggingface.co/Baptlem/UCDR-Net_models)
 
 """
 
@@ -74,7 +74,7 @@ def create_key(seed=0):
 
 def load_controlnet(controlnet_version):
     controlnet, controlnet_params = FlaxControlNetModel.from_pretrained(
-        "Baptlem/baptlem-controlnet",
+        "Baptlem/UCDR-Net_models",
         subfolder=controlnet_version,
         from_flax=True,
         dtype=jnp.float32,
@@ -104,7 +104,7 @@ def load_sb_pipe(controlnet_version, sb_path="runwayml/stable-diffusion-v1-5"):
 
     
 
-controlnet_path = "Baptlem/baptlem-controlnet"
+controlnet_path = "Baptlem/UCDR-Net_models"
 controlnet_version = "coyo-500k"
 
 # Constants
@@ -252,7 +252,7 @@ def create_demo(process, max_images=12, default_num_images=4):
                     model = gr.Dropdown(choices=["coyo-500k", "bridge-2M", "coyo1M-bridge2M", "coyo2M-bridge325k"],
                                         value="coyo-500k",
                                         label="Model used for inference", 
-                                        info="Find every models at https://huggingface.co/Baptlem/baptlem-controlnet")
+                                        info="Find every models at https://huggingface.co/Baptlem/UCDR-Net_models")
                     seed = gr.Slider(label='Seed',
                                      minimum=-1,
                                      maximum=2147483647,