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mrm8488/distilbert-base-multi-cased-finetuned-typo-detection
distilbert-base-multi-cased-finetuned-typo-detection is a token classification model from mrm8488. Use it when you need labels on individual words, such as names. It is set up for transformers.
distilbert-base-multilingual-cased fine-tuned on GitHub Typo Corpus for typo detection (using NER style)
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From the Hugging Face model README
distilbert-base-multilingual-cased fine-tuned on GitHub Typo Corpus for typo detection (using NER style)
Dataset: GitHub Typo Corpus 📚 for 15 languages
Fine-tune script on NER dataset provided by Huggingface 🏋️♂️
| Metric | # score |
|---|---|
| F1 | 93.51 |
| Precision | 96.08 |
| Recall | 91.06 |
Fast usage with pipelines 🧪
from transformers import pipeline
typo_checker = pipeline(
"ner",
model="mrm8488/distilbert-base-multi-cased-finetuned-typo-detection",
tokenizer="mrm8488/distilbert-base-multi-cased-finetuned-typo-detection"
)
result = typo_checker("Adddd validation midelware")
result[1:-1]
# Output:
[{'entity': 'ok', 'score': 0.7128152847290039, 'word': 'add'},
{'entity': 'typo', 'score': 0.5388424396514893, 'word': '##dd'},
{'entity': 'ok', 'score': 0.94792640209198, 'word': 'validation'},
{'entity': 'typo', 'score': 0.5839331746101379, 'word': 'mid'},
{'entity': 'ok', 'score': 0.5195121765136719, 'word': '##el'},
{'entity': 'ok', 'score': 0.7222476601600647, 'word': '##ware'}]
It works🎉! We typed wrong Add and middleware
Created by Manuel Romero/@mrm8488
Made with <span style="color: #e25555;">♥</span> in Spain