Update app.py

app.py

@@ -18,8 +18,8 @@ def generate(prompt):
     pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16").to("cuda")
     # Ensure sampler uses "trailing" timesteps and "sample" prediction type.
     pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", prediction_type="sample")
-    image = pipe(prompt, num_inference_steps=1, guidance_scale=0)
-    return image
+    image = pipe(prompt, num_inference_steps=1, guidance_scale=0).images[0]
+    return images[0]
 # Ensure using the same inference steps as the loaded model and CFG set to 0.
 
 # @spaces.GPU