| --- |
| language: |
| - en |
| license: mit |
| widget: |
| - text: "lets do a comparsion" |
| example_title: "1" |
| - text: "Their going to be here so0n" |
| example_title: "2" |
| - text: "ze shop is cloed due to covid 19" |
| example_title: "3" |
| metrics: |
| - cer |
| --- |
| |
| This is an experimental model that should fix your typos and punctuation. |
| If you like to run your own experiments or train for a different language, have a look at [the code](https://github.com/oliverguhr/spelling). |
|
|
|
|
| ## Model description |
|
|
| This is a proof of concept spelling correction model for English. |
|
|
| ## Intended uses & limitations |
|
|
| This project is work in progress, be aware that the model can produce artefacts. |
| You can test the model using the pipeline-interface: |
|
|
| ```python |
| from transformers import pipeline |
| |
| fix_spelling = pipeline("text2text-generation",model="oliverguhr/spelling-correction-english-base") |
| |
| print(fix_spelling("lets do a comparsion",max_length=2048)) |
| ``` |
|
|
