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- Token-level differential privacy for LLMs - Integration with Document Privacy API - Comprehensive test suite and documentation - Examples and Jupyter notebook included
37 lines
1.3 KiB
Markdown
37 lines
1.3 KiB
Markdown
# Changelog
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All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [Unreleased]
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## [0.1.0] - 2025-01-01
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### Added
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- Initial release of DP-Fusion-Lib
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- `DPFusion` class for differentially private text generation
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- Message-based context building with `add_message()`
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- Direct context generation with `generate()`
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- Token-level generation with `generate_from_tokens()`
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- `Tagger` class for automatic private phrase extraction
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- Integration with Document Privacy API
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- Support for multiple document types (HEALTH, FINANCE, LEGAL)
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- Privacy accounting functions
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- `compute_epsilon_single_group()` for single-group privacy guarantees
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- `compute_dp_epsilon()` for multi-group scenarios
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- Utility functions for advanced usage
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- `compute_renyi_divergence_clipped_symmetric()` for divergence computation
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- `find_lambda()` for binary search of mixing parameter
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- `replace_sequences_with_placeholder_fast()` for token-level redaction
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- Support for HuggingFace transformers models
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- Incremental decoding with KV-cache optimization
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- Comprehensive documentation and examples
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### Dependencies
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- PyTorch >= 2.0.0
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- Transformers >= 4.25.0
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- Requests >= 2.25.0
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