MVP

MVP 模型是由 Tianyi Tang、Junyi Li、Wayne Xin Zhao 和 Ji-Rong Wen 在 MVP: Multi-task Supervised Pre-training for Natural Language Generation 年提出的。

可以在 https://github.com/RUCAIBox/MVP 找到详细的信息和说明。

模型描述

MVP 是使用混合标记数据集进行有监督预训练的，它遵循标准的 Transformer 编码器-解码器架构。

MVP 是专门为自然语言生成而设计的，可以适应各种生成任务，包括但不限于摘要、数据到文本生成、开放式对话系统、故事生成、问答、问题生成、任务导向对话系统、常识生成、释义生成、文本风格转换和文本简化。我们的模型也可以适应自然语言理解任务，如序列分类和（抽取式）问答。

示例

对于摘要：

>>> from transformers import MvpTokenizer, MvpForConditionalGeneration

>>> tokenizer = MvpTokenizer.from_pretrained("RUCAIBox/mvp")
>>> model = MvpForConditionalGeneration.from_pretrained("RUCAIBox/mvp")

>>> inputs = tokenizer(
...     "Summarize: You may want to stick it to your boss and leave your job, but don't do it if these are your reasons.",
...     return_tensors="pt",
... )
>>> generated_ids = model.generate(**inputs)
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
["Why You Shouldn't Quit Your Job"]

对于数据到文本生成：

>>> from transformers import MvpTokenizerFast, MvpForConditionalGeneration

>>> tokenizer = MvpTokenizerFast.from_pretrained("RUCAIBox/mvp")
>>> model = MvpForConditionalGeneration.from_pretrained("RUCAIBox/mvp")

>>> 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)
['Stan Lee created the character of Iron Man, a fictional superhero appearing in American comic']

引用

@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},
}

作者:

AI Box

数据集大小:

1.52 GB

MVP

模型描述

示例

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