Cuda and Seed

app.py

@@ -15,7 +15,7 @@ def generate_image(prompt, negative_prompt, seed, width, height, guidance_scale,
         "playgroundai/playground-v2.5-1024px-aesthetic",
         torch_dtype=torch.float16,
         variant="fp16",
-    ).to("mps")
+    ).to("cuda")
 
     # # Optional: Use DPM++ 2M Karras scheduler for crisper fine details
     pipe.scheduler = EDMDPMSolverMultistepScheduler()
@@ -23,9 +23,9 @@ def generate_image(prompt, negative_prompt, seed, width, height, guidance_scale,
     # Check seed
     generator = None
     if seed == -1:
-        generator = torch.Generator("mps").manual_seed(12167262721866862)
+        generator = torch.Generator("cuda").manual_seed(12167262721866862)
     else:
-        generator = torch.Generator("mps").manual_seed(seed)
+        generator = torch.Generator("cuda").manual_seed(seed)
     image = pipe(prompt=prompt, num_inference_steps=steps, negative_prompt=negative_prompt, height=height, 
                  generator=generator, width=width, guidance_scale=guidance_scale).images[0]
     print('Image generated...')
@@ -47,7 +47,7 @@ iface = gr.Interface(
     inputs=[
         gr.Textbox(lines=4, placeholder="Enter your prompt"),
         gr.Textbox(lines=4, placeholder="Enter a negative prompt"),
-        gr.Slider(minimum=-1, maximum=982983949928455, value=-1, label="Seed"),
+        gr.Slider(minimum=-1, maximum=100000000, value=-1, label="Seed"),
         gr.Slider(minimum=720, maximum=1280, value=1024, label="Width"),
         gr.Slider(minimum=720, maximum=1280, value=1024, label="Height"),
         gr.Slider(minimum=1, maximum=10, value=3, label="Guidance Scale"),