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  license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ language:
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+ - en
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+ - de
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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: EN 1
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+ - text: Their going to be here so0n
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+ example_title: EN 2
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+ - text: das idst ein neuZr test
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+ example_title: DE 1
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+ - text: >-
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+ ein dransformer isd ein mthode mit der ein compuder eine volge von zeichn
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+ übersetz
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+ example_title: DE 2
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+ - text: can we mix the languages können wir die sprachen mischen
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+ example_title: EN and DE
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+ metrics:
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+ - cer
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+ pipeline_tag: text2text-generation
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  ---
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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, take a look at [the code](https://github.com/oliverguhr/spelling).
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+
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+
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+ ## Model description
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+
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+ This is a proof of concept **spelling correction model for English and German**.
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+
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+ ## Intended uses & limitations
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+
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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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+
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+ ```python
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+ from transformers import pipeline
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+
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+ fix_spelling_pipeline = pipeline("text2text-generation",model="oliverguhr/spelling-correction-multilingual-base")
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+ def fix_spelling(text, max_length = 256):
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+ return fix_spelling_pipeline("fix:"+text,max_length = max_length)
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+
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+ print(fix_spelling_pipeline("can we mix the languages können wir die sprachen mischen",max_length=2048))
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+ ```