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model_cards/mrm8488/distilbert-base-multi-cased-finetuned-typo-detection/README.md

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+---
+language: multilingual
+thumbnail:
+---
+
+# DISTILBERT 🌎 + Typo Detection ✍❌✍✔
+
+[distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) fine-tuned on [GitHub Typo Corpus](https://github.com/mhagiwara/github-typo-corpus) for **typo detection** (using *NER* style)
+
+## Details of the downstream task (Typo detection as NER)
+
+- Dataset: [GitHub Typo Corpus](https://github.com/mhagiwara/github-typo-corpus) 📚 for 15 languages
+
+- [Fine-tune script on NER dataset provided by Huggingface](https://github.com/huggingface/transformers/blob/master/examples/run_ner.py) 🏋️‍♂️
+
+## Metrics on test set 📋
+
+|  Metric   |  # score  |
+| :-------: | :-------: |
+|    F1     | **93.51** |
+| Precision | **96.08** |
+|  Recall   | **91.06** |
+
+## Model in action 🔨
+
+Fast usage with **pipelines** 🧪
+
+```python
+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](https://twitter.com/mrm8488)
+
+> Made with <span style="color: #e25555;">&hearts;</span> in Spain