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