coedit-large
Maintainer: grammarly
94
๐งช
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The coedit-large model is a large language model developed by Grammarly that has been fine-tuned on the CoEdIT dataset for text editing tasks. It is based on the google/flan-t5-large model, a version of the T5 language model that has been further trained on a variety of instruction-based tasks. Compared to the original T5 model, the FLAN-T5 models like coedit-large have shown stronger few-shot performance across a wide range of tasks.
Model inputs and outputs
Inputs
- Original text: The original text that needs to be edited.
- Edit instruction: A natural language description of the desired edits to be made to the original text.
Outputs
- Edited text: The model's generated version of the original text, incorporating the specified edits.
Capabilities
The coedit-large model is particularly skilled at text revision and editing tasks. Given an original piece of text and an instruction describing the desired changes, the model can generate an updated version of the text that implements those edits. This includes fixing grammatical errors, improving clarity and style, and making other targeted modifications to the input.
What can I use it for?
The coedit-large model could be useful for a variety of text-editing applications, such as:
- Automated proofreading and copy-editing
- Rephrasing and paraphrasing text
- Enhancing the quality of user-generated content
- Streamlining the editorial process for writers and content creators
You may also be interested in the ,[object Object], model, another powerful text-to-text transformer that excels at a wide range of natural language processing tasks.
Things to try
One interesting aspect of the coedit-large model is its ability to handle diverse edit instructions. Rather than just fixing predefined types of errors, the model can understand and implement more open-ended revisions described in natural language. This makes it a flexible tool for iteratively refining and polishing text. You could try providing the model with various types of editing prompts, from simple grammar and spelling corrections to more complex stylistic changes, and see how it responds.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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