模型:
RUCAIBox/mtl-data-to-text
MTL-data-to-text模型是由Tianyi Tang,Junyi Li,Wayne Xin Zhao和Ji-Rong Wen于 MVP: Multi-task Supervised Pre-training for Natural Language Generation 提出的。
详细信息和说明可以在 https://github.com/RUCAIBox/MVP 中找到。
MTL-data-to-text是通过使用混合标记的data-to-text数据集进行有监督预训练的。它是我们主要模型( MVP )的一种变体。它遵循标准的Transformer编码器-解码器架构。
MTL-data-to-text专门用于数据到文本生成任务,例如KG到文本生成(WebNLG,DART),表格到文本生成(WikiBio,ToTTo)和MR到文本生成(E2E)。
>>> from transformers import MvpTokenizer, MvpForConditionalGeneration >>> tokenizer = MvpTokenizer.from_pretrained("RUCAIBox/mvp") >>> model = MvpForConditionalGeneration.from_pretrained("RUCAIBox/mtl-data-to-text") >>> inputs = tokenizer( ... "Describe the following data: Iron Man | instance of | Superhero [SEP] Stan Lee | creator | Iron Man", ... return_tensors="pt", ... ) >>> generated_ids = model.generate(**inputs) >>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True) ['Iron Man is a fictional superhero appearing in American comic books published by Marvel Comics.']
MVP: https://huggingface.co/RUCAIBox/mvp 。
Prompt-based models:
Multi-task models:
@article{tang2022mvp, title={MVP: Multi-task Supervised Pre-training for Natural Language Generation}, author={Tang, Tianyi and Li, Junyi and Zhao, Wayne Xin and Wen, Ji-Rong}, journal={arXiv preprint arXiv:2206.12131}, year={2022}, url={https://arxiv.org/abs/2206.12131}, }