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.gitattributes

@@ -57,3 +57,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+models/wordseg_c2_crf.crfsuite filter=lfs diff=lfs merge=lfs -text
+pos_data/combined_pos_seed.csv filter=lfs diff=lfs merge=lfs -text
+segmentation/segmentation.mmap filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,68 @@
----
-license: mit
----
+# myspellchecker-resources
+
+Build-time resources for [myspellchecker](https://github.com/thettwe/myspellchecker) - Myanmar language spell checker.
+
+## Overview
+
+This repository hosts large binary files required by myspellchecker that are too large to bundle with the Python package. Files are downloaded automatically on first use.
+
+## Contents
+
+### segmentation/
+- **segmentation.mmap** (100MB) - Memory-mapped dictionary containing unigram and bigram log probabilities for Myanmar word segmentation using Viterbi algorithm.
+
+### models/
+- **wordseg_c2_crf.crfsuite** (3.2MB) - Conditional Random Fields model for syllable-based word tokenization.
+
+### pos_data/
+- **combined_pos_seed.csv** (15MB) - POS-tagged Myanmar words for grammar checking.
+
+## Technical Notes
+
+### .bin to .mmap Conversion
+
+The segmentation dictionary has been converted from pickle-based `.bin` files to memory-mapped `.mmap` format for:
+
+- **Memory Efficiency** - Lazy loading without loading entire file into RAM
+- **Fork-Safe** - Copy-on-Write (COW) semantics for multiprocessing
+- **Faster Startup** - No pickle deserialization overhead
+- **Security** - Eliminates pickle arbitrary code execution vulnerabilities
+- **Reduced Size** - 100MB consolidated vs 315MB separate .bin files
+
+## Credits & Attribution
+
+### myWord Project
+
+The word segmentation dictionary (`segmentation.mmap`) is derived from the **myWord** project:
+
+- **Repository**: https://github.com/ye-kyaw-thu/myWord
+- **Author**: Ye Kyaw Thu
+- **Description**: Myanmar word segmentation using statistical methods with Viterbi algorithm
+
+We are grateful to the myWord project for providing the foundational word frequency data that powers Myanmar text segmentation.
+
+### myTokenize Project
+
+The CRF model and tokenization framework are based on the **myTokenize** library:
+
+- **Repository**: https://github.com/ye-kyaw-thu/myTokenize
+- **Author**: Ye Kyaw Thu
+
+## Usage
+
+Resources are downloaded automatically by myspellchecker:
+
+```python
+from myspellchecker import SpellChecker
+
+# Resources download automatically on first use
+checker = SpellChecker()
+```
+
+## Cache Location
+
+Downloaded resources are cached at: `~/.cache/myspellchecker/resources/`
+
+## License
+
+These resources are provided under the same license terms as the original projects. Please refer to the original repositories for specific licensing information.

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