reviewer feedback

Author: sayakpaul

examples/dreambooth/train_dreambooth_lora_qwen_image.py

@@ -140,7 +140,7 @@ def save_model_card(
     model_card = load_or_create_model_card(
         repo_id_or_path=repo_id,
         from_training=True,
-        license="mit",  # TODO: Which license is this gonna be?
+        license="apache-2.0",
         base_model=base_model,
         prompt=instance_prompt,
         model_description=model_description,

src/diffusers/loaders/lora_pipeline.py

@@ -6706,7 +6706,7 @@ def load_lora_weights(
         )
 
     @classmethod
-    # Copied from diffusers.loaders.lora_pipeline.SD3LoraLoaderMixin.load_lora_into_transformer with SD3Transformer2DModel->SanaTransformer2DModel
+    # Copied from diffusers.loaders.lora_pipeline.SD3LoraLoaderMixin.load_lora_into_transformer with SD3Transformer2DModel->QwenImageTransformer2DModel
     def load_lora_into_transformer(
         cls,
         state_dict,
@@ -6725,7 +6725,7 @@ def load_lora_into_transformer(
                 A standard state dict containing the lora layer parameters. The keys can either be indexed directly
                 into the unet or prefixed with an additional `unet` which can be used to distinguish between text
                 encoder lora layers.
-            transformer (`SanaTransformer2DModel`):
+            transformer (`QwenImageTransformer2DModel`):
                 The Transformer model to load the LoRA layers into.
             adapter_name (`str`, *optional*):
                 Adapter name to be used for referencing the loaded adapter model. If not specified, it will use