metadata
license: apache-2.0
language:
- en
tags:
- text-generation
- text2text-generation
pipeline_tag: text2text-generation
widget:
- text: >-
Given the story title: I think all public schools should have a uniform
dress code.
example_title: Example1
- text: >-
Given the story title: My girlfriend and I decided to move to a new state.
We packed everything in our cars and drove there.
example_title: Example2
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.']