[bugfix] Fix the issue that will save the model card if push to hub is not applied in HiDream

examples/dreambooth/README_qwen.md

@@ -75,9 +75,9 @@ Now, we can launch training using:
 ```bash
 export MODEL_NAME="Qwen/Qwen-Image"
 export INSTANCE_DIR="dog"
-export OUTPUT_DIR="trained-sana-lora"
+export OUTPUT_DIR="trained-qwenimage-lora"
 
-accelerate launch train_dreambooth_lora_sana.py \
+accelerate launch train_dreambooth_lora_qwenimage.py \
   --pretrained_model_name_or_path=$MODEL_NAME  \
   --instance_data_dir=$INSTANCE_DIR \
   --output_dir=$OUTPUT_DIR \

examples/dreambooth/train_dreambooth_lora_hidream.py

@@ -1771,16 +1771,16 @@ def get_sigmas(timesteps, n_dim=4, dtype=torch.float32):
             free_memory()
 
         validation_prompt = args.validation_prompt if args.validation_prompt else args.final_validation_prompt
-        save_model_card(
-            (args.hub_model_id or Path(args.output_dir).name) if not args.push_to_hub else repo_id,
-            images=images,
-            base_model=args.pretrained_model_name_or_path,
-            instance_prompt=args.instance_prompt,
-            validation_prompt=validation_prompt,
-            repo_folder=args.output_dir,
-        )
 
         if args.push_to_hub:
+            save_model_card(
+                (args.hub_model_id or Path(args.output_dir).name) if not args.push_to_hub else repo_id,
+                images=images,
+                base_model=args.pretrained_model_name_or_path,
+                instance_prompt=args.instance_prompt,
+                validation_prompt=validation_prompt,
+                repo_folder=args.output_dir,
+            )
             upload_folder(
                 repo_id=repo_id,
                 folder_path=args.output_dir,
@@ -1789,6 +1789,7 @@ def get_sigmas(timesteps, n_dim=4, dtype=torch.float32):
             )
 
         images = None
+        del pipeline
 
     accelerator.end_training()