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