MIT License

Copyright 2012 Kay Zhu

Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
of the Software, and to permit persons to whom the Software is furnished to do
so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

---

# LLSHash Enhancements

This project includes modifications to the original LSHash implementation by Kay Zhu to better suit the process of data deduplication for training large language models by Mostafa Abdolmaleki.

**Modifications Include:**

- Addition of a direct duplicate finder function.
- Batch processing for improved performance.
- Parallel processing on CPUs and clusters using Ray.
- Integration with Hugging Face's Transformers and Datasets libraries.
- Offloading and reloading data using disk storage for efficient RAM management.
- Transition to NumPy's advanced storage management.
- Removal of Redis to align with the package's new objectives.
- Adoption of modern best practices, including type annotations and removal of deprecated package support.