Update app.py

app.py

@@ -4,8 +4,17 @@ import gradio as gr
 
 def load_pipeline():
     
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    dtype  = torch.float16 if device == "cuda" else torch.float32
+   if torch.cuda.is_available():
+        device = "cuda"
+    elif hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
+        device = "mps"
+    else:
+        device = "cpu"
+
+    # Use float16 on any accelerator, float32 on CPU
+    dtype = torch.float16 if device != "cpu" else torch.float32
+    print(f"Using device: {device}, dtype: {dtype}")
+
 
     pipe = StableDiffusionPipeline.from_pretrained(
         "runwayml/stable-diffusion-v1-5",