>>> from transformers import BertTokenizer, GPT2LMHeadModel,TextGenerationPipeline
>>> tokenizer = BertTokenizer.from_pretrained("snzhang/GPT2-Poem-Small")
>>> model = GPT2LMHeadModel.from_pretrained("snzhang/GPT2-Poem-Small")
>>> text_generator = TextGenerationPipeline(model, tokenizer)   
>>> text_generator("笔底江山助磅礴", max_length=50, do_sample=True)
    [{'generated_text':'笔底江山助磅礴，万卷诗书见成章。'}]

And you can add the prefix "(唐诗：your title)"、"(宋词：your title)" and "(对联)" to make generation more precise.

Training data

Training data contains 71,334 Chinese ancient poems and couplets which are collected by Chinese Poetry and Couplet Dataset

More Details

You can get more details in GPT2-Poem-Small