Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import torchvision
+imp
+ort torch
+model = torch.hub.load(
+    "ndahlquist/pytorch-hub-stylegan:0.0.1",
+    "style_gan",
+    pretrained=True)
+def iface(name):
+  model.eval()
+  device = 'cuda:0' if torch.cuda.is_available() else 'cpu'
+  model.to(device)
+  latents = torch.randn(1, 512, device=device)
+  with torch.no_grad():
+    img = model(latents)
+    img = (img.clamp(-1, 1) + 1) / 2.0
+    img2=img.numpy()
+    img3=img2.squeeze()
+    img4 = img3.swapaxes(0,1)
+    img5=img4.swapaxes(1,2)
+  out= img5
+  return out
+demo = gr.Interface(fn=iface,inputs='text', outputs='image')
+demo.launch()
+