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README.md

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----
-license: mit
----
+---
+license: mit
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- typo
+pretty_name: M2M
+size_categories:
+- 10K<n<100K
+---
+
+# Clear Spelling Dataset
+
+## Overview
+
+The **Clear Spelling Dataset** is a carefully crafted collection of **100,000 unique English spelling mistakes and their correct forms**, intended for training high-quality typo correction and spell checking AI models. It covers various types of common mistakes observed frequently in real-world scenarios, such as:
+
+- Keyboard adjacency typos
+- Letter swaps and omissions
+- Duplicate characters
+- Phonetic substitution errors
+- Commonly confused homophones (e.g., "their" vs. "there")
+
+## Dataset Format
+
+The dataset is provided in **CSV format** with two clearly defined columns:
+
+| Column   | Description                                 | Example             |
+|----------|---------------------------------------------|---------------------|
+| `error`  | The misspelled or incorrect word or phrase  | "teh"              |
+| `correct`| The correct word or intended phrase         | "the"              |
+
+## Usage
+
+This dataset is ideal for:
+
+- Training and fine-tuning **typo correction** models
+- Benchmarking **spell-checking algorithms**
+- Enhancing NLP model robustness to real-world noisy input
+
+## Quality Assurance
+
+- **No duplicates:** Each (error, correct) pair is unique.
+- **Hand-curated seed set:** Includes hundreds of common misspellings verified against real-world usage patterns.
+- **Realistic noise generation:** Uses realistic error transformations mimicking genuine human typing behavior.
+
+## License (MIT)
+
+This dataset is released under the permissive **MIT License**, which allows commercial and non-commercial use, distribution, and modification. Attribution is required:
+
+
+## Citation
+
+If you use this dataset in your research or projects, please provide attribution similar to:
+
+```
+This [your project type] uses the Mistake to Learning dataset by ProCreations.
+```
+
+Enjoy training your typo-correction models!