Change to SD2-Community mirror due to SD2.1 depracation

app.py

@@ -16,8 +16,8 @@ if os.getenv("SPACES_ZERO_GPU") == "true":
     os.environ["SPACES_ZERO_GPU"] = "1"
 
 
-avail_models = {'512x512': load_model('stabilityai/stable-diffusion-2-1-base', 1000, float16=True, device=torch.device("cpu"), compile=False)[0],
-                '768x768': load_model('stabilityai/stable-diffusion-2-1', 1000, float16=True, device=torch.device("cpu"), compile=False)[0]
+avail_models = {'512x512': load_model('sd2-community/stable-diffusion-2-1-base', 1000, float16=True, device=torch.device("cpu"), compile=False)[0],
+                '768x768': load_model('sd2-community/stable-diffusion-2-1', 1000, float16=True, device=torch.device("cpu"), compile=False)[0]
                }
 
 compression_func = partial(latent_DDCM_compression.main, avail_models=avail_models)
@@ -88,7 +88,8 @@ DDCM can easily be utilized for perceptual image compression, as well as for sol
 </br></br>
 The tabs below correspond to demos of different practical applications. Open each tab to see the application's specific instructions.
 </br></br>
-<b>Note: The demos below rely on relatively old pre-trained diffusion models such as Stable Diffusion 2.1, simply for the purpose of demonstrating the capabilities of DDCM. Feel free to implement our DDCM-based methods using newer diffusion models to further improve performance.</b>
+<b>Note: The demos below rely on relatively old pre-trained diffusion models such as Stable Diffusion 2.1 
+(Mirrored by <a href="https://huggingface.co/sd2-community">sd2-community</a>), simply for the purpose of demonstrating the capabilities of DDCM. Feel free to implement our DDCM-based methods using newer diffusion models to further improve performance.</b>
 """
 
 article = r"""