Update app.py

app.py

@@ -29,17 +29,9 @@ class Generator(nn.Module):
         return output
 
 
-model = Generator()
-weights_path = hf_hub_download('nateraw/cryptopunks-gan', 'generator.pth')
-model.load_state_dict(torch.load(weights_path, map_location=torch.device('cpu'))) # Use 'cuda' if you have a GPU available
-
-
-def predict(seed, num_punks):
-    torch.manual_seed(seed)
-    z = torch.randn(num_punks, 100, 1, 1)
-    punks = model(z)
-    save_image(punks, "punks.png", normalize=True)
-    return 'punks.png'
+def predict(body, hair, top, bottom):
+    name = str(body) + str(hair) + str(top) + str(bottom)
+    return name
 
 gr.Interface(
     predict,
@@ -49,7 +41,6 @@ gr.Interface(
         gr.Slider(0, 3, label='Top', step=1, default=0),
         gr.Slider(0, 4, label='Bottom', step=1, default=0),
     ],
-    outputs="image",
-    examples=[[123, 15], [42, 29], [456, 8], [1337, 35]],
+    outputs="name",
     live=True,
 ).launch(cache_examples=True)