models

app.py

@@ -19,12 +19,13 @@ import gradio as gr
 import base64
 
 modelieo=[
- 'nathanReitinger/MNIST-diffusion',
- 'nathanReitinger/MNIST-diffusion-oneImage',
- 'nathanReitinger/MNIST-GAN',
- 'nathanReitinger/MNIST-GAN-noDropout',
- 'nathanReitinger/FASHION-diffusion-oneImage'
-  ]
+  'nathanReitinger/MNIST-diffusion',
+  'nathanReitinger/MNIST-diffusion-oneImage',
+  'nathanReitinger/MNIST-GAN',
+  'nathanReitinger/MNIST-GAN-noDropout',
+  'nathanReitinger/FASHION-diffusion-oneImage',
+  'nathanReitinger/FASHION-diffusion'
+]
 
 def get_sims(gen_filepath, gen_label, file_path, hunting_time_limit, data_type):
   if data_type == 'mnist':
@@ -249,10 +250,10 @@ 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-diffuion-oneImage'], 
-    "Class (Architecture)"  : ['UNet2DModel', 'UNet2DModel', 'Sequential', 'Sequential', 'UNet2DModel'], 
-    "Dataset Examples"      : [60000, 1, 60000, 60000, 1], 
-    "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)']
+    "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']
 }) 
 
 # Applying style to highlight the maximum value in each row