Update app.py

app.py

@@ -304,13 +304,8 @@ def sample_then_run():
     steps = 25
     image = inference( prompt, negative_prompt, cfg, steps, seed)
     torch.save(network.value.proj, "model.pt" )
-    net = LoRAw2w( sample, mean, std, v, 
-                    unet,
-                    rank=1,
-                    multiplier=1.0,
-                    alpha=27.0,
-                    train_method="xattn-strict"
-                ).to(device.value, torch.bfloat16)
+    net = torch.load("model.pt").cpu()
+    print(net)
     
     return image, "model.pt", net   #, network.value.cpu()