train_text_to_image_sdxl.py fail resume from checkpoint and also can not load for infer

### Describe the bug

I try to finetune a SDXL model. But meet same questions.

I can not resume from a checkpoint model and the error is shown as follows:

[rank0]: load_checkpoint_in_model(
[rank0]: File "/mnt/wangxuekuan/miniconda3/envs/sdxl/lib/python3.8/site-packages/accelerate/utils/modeling.py", line 1637, in load_checkpoint_in_model
[rank0]: raise ValueError(
[rank0]: ValueError: /mnt/wangxuekuan/finetune/all/sdxl-exp0/checkpoint-10000 is not a folder containing a `.index.json` file or a pytorch_model.bin or a model.safetensors file

Here is model path:
(sdxl) wangxuekuan@ucloud-9:/mnt/wangxuekuan/diffusers/examples/text_to_image$ ls /mnt/wangxuekuan/finetune/all/sdxl-exp0/checkpoint-10000/unet/
config.json diffusion_pytorch_model-00002-of-00002.safetensors
diffusion_pytorch_model-00001-of-00002.safetensors diffusion_pytorch_model.safetensors.index.json

Meanwhile, I want to test the checkpoint, is also fail in loading checkpoint.
unet = UNet2DConditionModel.from_pretrained(model_path, subfolder="unet")
pipe = DiffusionPipeline.from_pretrained(model_path, unet=unet, safety_checker=None)

same error !

### Reproduction

infer code:
unet = UNet2DConditionModel.from_pretrained(model_path, subfolder="unet")
pipe = DiffusionPipeline.from_pretrained(model_path, unet=unet, safety_checker=None)

train shell.

export MODEL_NAME="stabilityai/stable-diffusion-xl-base-1.0"
export VAE_NAME="madebyollin/sdxl-vae-fp16-fix"
export DATASET_NAME="lambdalabs/naruto-blip-captions"
export OUTPUT_DIR="/mnt/wangxuekuan/finetune/all/sdxl-exp0"
export RESUME_FROM_CHECKPOINT="/mnt/wangxuekuan/finetune/all/sdxl-exp0/checkpoint-10000"
export DATASET_NAME="selected_16" #"/mnt/xys/dataset/character/all_in_one_0419/"

accelerate launch train_text_to_image_sdxl.py \
--pretrained_model_name_or_path=$MODEL_NAME \
--pretrained_vae_model_name_or_path=$VAE_NAME \
--train_data_dir=$DATASET_NAME --caption_column="text" \
--resume_from_checkpoint=$RESUME_FROM_CHECKPOINT \
--enable_xformers_memory_efficient_attention \
--resolution=512 --center_crop --random_flip \
--proportion_empty_prompts=0.2 \
--train_batch_size=1 \
--gradient_accumulation_steps=4 --gradient_checkpointing \
--max_train_steps=1000000 \
--use_8bit_adam \
--learning_rate=1e-06 --lr_scheduler="constant" --lr_warmup_steps=0 \
--mixed_precision="fp16" \
--validation_prompt="a cute Sundar Pichai creature" --validation_epochs 5 \
--checkpointing_steps=50 \
--output_dir=$OUTPUT_DIR
# --push_to_hub

### Logs

_No response_

### System Info

python3.8
diffusers-0.30
A100-80G

### Who can help?

_No response_

Comienza con examples/text_to_image/train_text_to_image_sdxl.py y reproduce el fallo utilizando el comando accelerate y la ruta del checkpoint proporcionados. Inspecciona cómo se gestionan el directorio del checkpoint y sus archivos UNet fragmentados para reanudar el entrenamiento y para la inferencia. Se considera terminado cuando el checkpoint mostrado puede reanudar el entrenamiento y cargarse mediante el código proporcionado de UNet2DConditionModel y DiffusionPipeline.

Escrito por el modelo de indexación a partir del texto del issue.