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src/pipeline.py

@@ -54,9 +54,10 @@ def load_pipeline() -> Pipeline:
     pipeline.to(memory_format=torch.channels_last)
     quantize_(pipeline.vae, int8_weight_only()) 
     pipeline.vae = my_partial_compile(pipeline.vae)
+    pipeline.transformer = torch.compile(pipeline.transformer)
     with torch.inference_mode():
         for _ in range(2):
-            pipeline("cat", num_inference_steps=4)
+            pipeline("cats running on a road with a dog chasing", num_inference_steps=4)
 
     return pipeline