This repository contains a fine-tuned multilingual DistilBERT model for Urdu real-word spelling correction.
The model was fine-tuned on aligned noisy/corrected Urdu text to predict the correct token using sentence context.
1from transformers import AutoTokenizer
2from transformers import AutoModelForTokenClassification
3
4tokenizer = AutoTokenizer.from_pretrained(
5 "HuzaifaQ-12/Urdu_spelling_correction"
6)
7
8model = AutoModelForTokenClassification.from_pretrained(
9 "HuzaifaQ-12/Urdu_spelling_correction"
10)
The complete project, methodology, preprocessing pipeline, report, and source code are available on GitHub:
This repository contains only the trained model weights and tokenizer files.
For implementation details, dataset preparation, evaluation, and methodology, see the GitHub repository.