we integrate C and A into a new C' in the following form.
C' = [c1, c2, ..., [HL], a1, ..., a|A|, [HL], ..., c|C|]

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
tokenizer = AutoTokenizer.from_pretrained("p208p2002/bart-drcd-qg-hl")

model = AutoModelForSeq2SeqLM.from_pretrained("p208p2002/bart-drcd-qg-hl")

usage: train_seq2seq_lm.py [-h]
                           [--base_model {bert-base-chinese,uer/bart-base-chinese-cluecorpussmall,p208p2002/bart-drcd-qg-hl}]
                           [-d {drcd}] [--batch_size BATCH_SIZE]
                           [--epoch EPOCH] [--lr LR] [--dev DEV] [--server]
                           [--run_test] [-fc FROM_CHECKPOINT]

optional arguments:
  -h, --help            show this help message and exit
  --base_model {bert-base-chinese,uer/bart-base-chinese-cluecorpussmall,p208p2002/bart-drcd-qg-hl}
  -d {drcd}, --dataset {drcd}
  --batch_size BATCH_SIZE
  --epoch EPOCH
  --lr LR
  --dev DEV
  --server
  --run_test
  -fc FROM_CHECKPOINT, --from_checkpoint FROM_CHECKPOINT

python train_seq2seq_lm.py --server --base_model p208p2002/bart-drcd-qg-hl

python train_xxx_lm.py --server --base_model YOUR_BASE_MODEL --from_checkpoint FROM_CHECKPOINT

curl --location --request POST 'http://127.0.0.1:5000/' \
--header 'Content-Type: application/x-www-form-urlencoded' \
--data-urlencode 'context=[HL]伊隆·里夫·馬斯克[HL]是一名企業家和商業大亨'

{"predict": "哪一個人是一名企業家和商業大亨?"}