from swift.llm import DatasetName, ModelType, SftArguments, sft_main
import os

os.environ['CUDA_VISIBLE_DEVICES'] = '0'

sft_args = SftArguments(
model_type=ModelType.qwen1half_7b_chat,
dataset=[DatasetName.ms_bench_mini],
train_dataset_sample=1000,
logging_steps=5,
max_length=2048,
learning_rate=5e-5,
warmup_ratio=0.4,
output_dir='output',
lora_target_modules=['ALL'],
self_cognition_sample=500,
model_name=['小黄', 'Xiao Huang'],
model_author=['魔搭', 'ModelScope'])
output = sft_main(sft_args)
best_model_checkpoint = output['best_model_checkpoint']
print(f'best_model_checkpoint: {best_model_checkpoint}')

魔搭免费A10 24G 微调qwen1half_7b_chat 执行完上面的代码，终端再执行下面的打印代码，Notebook 量化的时候就503代码错误了，这个问题该如何解决？

print(f'''CUDA_VISIBLE_DEVICES=0 swift export \
--ckpt_dir {best_model_checkpoint} \
--quant_bits 4 --quant_method awq \
--merge_lora true''')