v2

app.py

@@ -40,7 +40,8 @@ def load_pipeline(model_id: str):
         pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch_dtype)
         # Load the LoRA weights into the U-Net.
         # This assumes that load_attn_procs loads the LoRA weights.
-        pipe.unet.load_attn_procs(model_id)
+        # pipe.unet.load_attn_procs(model_id)
+        pipe.load_lora_weights(model_id)
     else:
         pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)