weight_name="adapter_model.safetensors"

app.py

@@ -41,7 +41,7 @@ def load_pipeline(model_id: str):
         # 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.load_lora_weights(model_id)
+        pipe.load_lora_weights(model_id, weight_name="adapter_model.safetensors")
     else:
         pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)