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<title>base-model/src/basemodel, branch v0.1.6</title>
<subtitle>BaseModel for HydroRoll </subtitle>
<id>https://git.hydroroll.team/base-model/atom?h=v0.1.6</id>
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<updated>2025-12-30T12:16:05Z</updated>
<entry>
<title>refactor: Refactor TRPG NER model SDK: restructure codebase into base_model_trpgner package, implement training and inference modules, and add model download functionality. Remove legacy training and utils modules. Enhance documentation and examples for better usability.</title>
<updated>2025-12-30T12:16:05Z</updated>
<author>
<name>HsiangNianian</name>
<email>i@jyunko.cn</email>
</author>
<published>2025-12-30T12:16:05Z</published>
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<entry>
<title>feat: Refactor and enhance TRPG NER model SDK</title>
<updated>2025-12-30T11:54:08Z</updated>
<author>
<name>HsiangNianian</name>
<email>i@jyunko.cn</email>
</author>
<published>2025-12-30T11:54:08Z</published>
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<id>urn:sha1:575114661ef9afb95df2a211e1d8498686340e6b</id>
<content type='text'>
- Removed deprecated `word_conll_to_char_conll.py` utility and integrated its functionality into the new `utils` module.
- Introduced a comprehensive GitHub Actions workflow for automated publishing to PyPI and GitHub Releases.
- Added `__init__.py` files to establish package structure for `basemodel`, `inference`, `training`, and `utils` modules.
- Implemented model downloading functionality in `download_model.py` to fetch pre-trained ONNX models.
- Developed `TRPGParser` class for ONNX-based inference, including methods for parsing TRPG logs.
- Created training utilities in `training/__init__.py` for NER model training with Hugging Face Transformers.
- Enhanced utility functions for CoNLL file parsing and dataset creation.
- Added command-line interface for converting CoNLL files to datasets with validation options.
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