MVP-story
The MVP-story model was proposed in MVP: Multi-task Supervised Pre-training for Natural Language Generation by Tianyi Tang, Junyi Li, Wayne Xin Zhao and Ji-Rong Wen.
The detailed information and instructions can be found https://github.com/RUCAIBox/MVP.
Model Description
MVP-story is a prompt-based model that MVP is further equipped with prompts pre-trained using labeled story generation datasets. It is a variant (MVP+S) of our main MVP model. It follows a Transformer encoder-decoder architecture with layer-wise prompts.
MVP-story is specially designed for story generation tasks, such as ROCStories and WritingPrompts.
Example
>>> from transformers import MvpTokenizer, MvpForConditionalGeneration
>>> tokenizer = MvpTokenizer.from_pretrained("RUCAIBox/mvp")
>>> model = MvpForConditionalGeneration.from_pretrained("RUCAIBox/mvp-story")
>>> inputs = tokenizer(
... "Given the story title: I think all public schools should have a uniform dress code.",
... return_tensors="pt",
... )
>>> generated_ids = model.generate(**inputs, max_length=1024)
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
['I think it would be a good idea to have uniform dress codes for all public schools. It would make it easier for students to dress appropriately.']
Related Models
MVP: https://huggingface.co/RUCAIBox/mvp.
Prompt-based models:
- MVP-multi-task: https://huggingface.co/RUCAIBox/mvp-multi-task.
- MVP-summarization: https://huggingface.co/RUCAIBox/mvp-summarization.
- MVP-open-dialog: https://huggingface.co/RUCAIBox/mvp-open-dialog.
- MVP-data-to-text: https://huggingface.co/RUCAIBox/mvp-data-to-text.
- MVP-story: https://huggingface.co/RUCAIBox/mvp-story.
- MVP-question-answering: https://huggingface.co/RUCAIBox/mvp-question-answering.
- MVP-question-generation: https://huggingface.co/RUCAIBox/mvp-question-generation.
- MVP-task-dialog: https://huggingface.co/RUCAIBox/mvp-task-dialog.
Multi-task models:
- MTL-summarization: https://huggingface.co/RUCAIBox/mtl-summarization.
- MTL-open-dialog: https://huggingface.co/RUCAIBox/mtl-open-dialog.
- MTL-data-to-text: https://huggingface.co/RUCAIBox/mtl-data-to-text.
- MTL-story: https://huggingface.co/RUCAIBox/mtl-story.
- MTL-question-answering: https://huggingface.co/RUCAIBox/mtl-question-answering.
- MTL-question-generation: https://huggingface.co/RUCAIBox/mtl-question-generation.
- MTL-task-dialog: https://huggingface.co/RUCAIBox/mtl-task-dialog.
Citation
@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},
}
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