coedit-large / README.md
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metadata
language:
  - en
license: cc-by-nc-4.0
datasets:
  - facebook/asset
  - wi_locness
  - GEM/wiki_auto_asset_turk
  - discofuse
  - zaemyung/IteraTeR_plus
  - jfleg
  - grammarly/coedit
metrics:
  - sari
  - bleu
  - accuracy
widget:
  - text: >-
      Fix the grammar: When I grow up, I start to understand what he said is
      quite right.
    example_title: Fluency
  - text: >-
      Make this text coherent: Their flight is weak. They run quickly through
      the tree canopy.
    example_title: Coherence
  - text: >-
      Rewrite to make this easier to understand: A storm surge is what
      forecasters consider a hurricane's most treacherous aspect.
    example_title: Simplification
  - text: 'Paraphrase this: Do you know where I was born?'
    example_title: Paraphrase
  - text: >-
      Write this more formally: omg i love that song im listening to it right
      now
    example_title: Formalize
  - text: 'Write in a more neutral way: The authors'' exposé on nutrition studies.'
    example_title: Neutralize

Model Card for CoEdIT-Large

This model was obtained by fine-tuning the corresponding google/flan-t5-large model on the CoEdIT dataset. Details of the dataset can be found in our paper and repository.

Paper: CoEdIT: Text Editing by Task-Specific Instruction Tuning

Authors: Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang

Model Details

Model Description

  • Language(s) (NLP): English
  • Finetuned from model: google/flan-t5-large

Model Sources

How to use

We make available the models presented in our paper.

Model Number of parameters
CoEdIT-large 770M
CoEdIT-xl 3B
CoEdIT-xxl 11B

Uses

Text Revision Task

Given an edit instruction and an original text, our model can generate the edited version of the text.

task_specs

Usage

from transformers import AutoTokenizer, T5ForConditionalGeneration

tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-large")
model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-large")
input_text = 'Fix grammatical errors in this sentence: When I grow up, I start to understand what he said is quite right.'
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
outputs = model.generate(input_ids, max_length=256)
edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

Software

https://github.com/vipulraheja/coedit

Citation

BibTeX:

@article{raheja2023coedit,
      title={CoEdIT: Text Editing by Task-Specific Instruction Tuning}, 
      author={Vipul Raheja and Dhruv Kumar and Ryan Koo and Dongyeop Kang},
      year={2023},
      eprint={2305.09857},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

APA: Raheja, V., Kumar, D., Koo, R., & Kang, D. (2023). CoEdIT: Text Editing by Task-Specific Instruction Tuning. ArXiv. /abs/2305.09857