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The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
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))
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