Instructions to use oliverguhr/spelling-correction-english-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oliverguhr/spelling-correction-english-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("oliverguhr/spelling-correction-english-base") model = AutoModelForSeq2SeqLM.from_pretrained("oliverguhr/spelling-correction-english-base") - Notebooks
- Google Colab
- Kaggle
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.
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:
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))
- Downloads last month
- 19,271
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support