diff --git a/skynet/dgpu.py b/skynet/dgpu.py
index a26336e..7b44d6c 100644
--- a/skynet/dgpu.py
+++ b/skynet/dgpu.py
@@ -56,7 +56,7 @@ def pipeline_for(algo: str, mem_fraction: float = 1.0):
 
     pipe.enable_vae_slicing()
 
-    return pipe.to("cuda")
+    return pipe.to('cuda')
 
 
 class DGPUComputeError(BaseException):
diff --git a/skynet/utils.py b/skynet/utils.py
index 0534160..06bba1d 100644
--- a/skynet/utils.py
+++ b/skynet/utils.py
@@ -64,18 +64,19 @@ def upscale(
     torch.backends.cudnn.allow_tf32 = True
 
     login(token=hf_token)
-    params = {
-        'torch_dtype': torch.float16,
-        'safety_checker': None
-    }
 
     pipe = StableDiffusionUpscalePipeline.from_pretrained(
-        'stabilityai/stable-diffusion-x4-upscaler', **params)
+        'stabilityai/stable-diffusion-x4-upscaler',
+        revision="fp16", torch_dtype=torch.float16)
+    pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(
+        pipe.scheduler.config)
+    pipe = pipe.to('cuda')
 
     prompt = prompt
     image = pipe(
         prompt,
-        image=Image.open(img_path)
+        image=Image.open(img_path).convert("RGB"),
+        num_inference_steps=steps
     ).images[0]
 
     image.save(output)