uer/gpt2

2023-09-30 16:06| 来源: 网络整理| 查看: 265

Chinese GPT2 Lyric Model Model description

The model is pre-trained by UER-py, which is introduced in this paper. Besides, the model could also be pre-trained by TencentPretrain introduced in this paper, which inherits UER-py to support models with parameters above one billion, and extends it to a multimodal pre-training framework.

The model is used to generate Chinese lyrics. You can download the model from the UER-py Modelzoo page, or GPT2-Chinese Github page, or via HuggingFace from the link gpt2-chinese-lyric

How to use

You can use the model directly with a pipeline for text generation:

>>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-lyric") >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-lyric") >>> text_generator = TextGenerationPipeline(model, tokenizer) >>> text_generator("最美的不是下雨天，是曾与你躲过雨的屋檐", max_length=100, do_sample=True) [{'generated_text': '最美的不是下雨天，是曾与你躲过雨的屋檐，下课铃声响起的瞬间，我们的笑脸，有太多回忆在浮现，是你总在我身边，不知道会不会再见，从现在开始到永远，想说的语言凝结成一句，不管我们是否能够兑现，想说的语言凝结'}] Training data

Training data contains 150,000 Chinese lyrics which are collected by Chinese-Lyric-Corpus and MusicLyricChatbot.

Training procedure

The model is pre-trained by UER-py on Tencent Cloud. We pre-train 100,000 steps with a sequence length of 512 on the basis of the pre-trained model gpt2-base-chinese-cluecorpussmall

python3 preprocess.py --corpus_path corpora/lyric.txt \ --vocab_path models/google_zh_vocab.txt \ --dataset_path lyric_dataset.pt --processes_num 32 \ --seq_length 512 --data_processor lm python3 pretrain.py --dataset_path lyric_dataset.pt \ --pretrained_model_path models/cluecorpussmall_gpt2_seq1024_model.bin-250000 \ --vocab_path models/google_zh_vocab.txt \ --config_path models/gpt2/config.json \ --output_model_path models/lyric_gpt2_model.bin \ --world_size 8 --gpu_ranks 0 1 2 3 4 5 6 7 \ --total_steps 100000 --save_checkpoint_steps 10000 --report_steps 5000 \ --learning_rate 5e-5 --batch_size 64

Finally, we convert the pre-trained model into Huggingface's format:

python3 scripts/convert_gpt2_from_uer_to_huggingface.py --input_model_path lyric_gpt2_model.bin-100000 \ --output_model_path pytorch_model.bin \ --layers_num 12 BibTeX entry and citation info @article{radford2019language, title={Language Models are Unsupervised Multitask Learners}, author={Radford, Alec and Wu, Jeff and Child, Rewon and Luan, David and Amodei, Dario and Sutskever, Ilya}, year={2019} } @article{zhao2019uer, title={UER: An Open-Source Toolkit for Pre-training Models}, author={Zhao, Zhe and Chen, Hui and Zhang, Jinbin and Zhao, Xin and Liu, Tao and Lu, Wei and Chen, Xi and Deng, Haotang and Ju, Qi and Du, Xiaoyong}, journal={EMNLP-IJCNLP 2019}, pages={241}, year={2019} } @article{zhao2023tencentpretrain, title={TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities}, author={Zhao, Zhe and Li, Yudong and Hou, Cheng and Zhao, Jing and others}, journal={ACL 2023}, pages={217}, year={2023} }

【本文地址】

uer/gpt2

uer/gpt2

今日新闻

推荐新闻