models

app.py

@@ -251,7 +251,7 @@ def TextToImage(Prompt,inference_steps, model):
   return [ai_gen, another_one]
 
 df = pd.DataFrame({
-    "Model"                 : ['MNIST-diffusion', 'MNIST-diffusion-oneImage', 'MNIST-GAN', 'MNIST-GAN-noDropout', 'FASHION-diffusion-oneImage', 'FASHION-diffusion'], 
+    "Model"                 : ['MNIST-diffusion', 'MNIST-diffusion-oneImage', 'MNIST-GAN', 'MNIST-GAN-noDropout', 'FASHION-diffuion-oneImage', 'FASHION-diffusion'], 
     "Class (Architecture)"  : ['UNet2DModel', 'UNet2DModel', 'Sequential', 'Sequential', 'UNet2DModel', 'UNet2DModel'], 
     "Dataset Examples"      : [60000, 1, 60000, 60000, 1, 60000], 
     "Notes"                 : ['Similar architecture as Stable Diffusion, different training data', 'Toy model, purposed to store protected content', 'GANs are not as likely to store protected content', 'less dropout, more copying?', 'same diffusion, different data (more variance in data)','larger diffusion training data, on FASHION dataset']