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chore(deps): upgrade trl (#537)
* deps: upgrade trl Signed-off-by: Will Johnson <mwjohnson728@gmail.com> * docs: offline data preprocessing note Signed-off-by: Will Johnson <mwjohnson728@gmail.com> --------- Signed-off-by: Will Johnson <mwjohnson728@gmail.com> Co-authored-by: Dushyant Behl <dushyantbehl@users.noreply.github.com>
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docs/offline-data-preprocessing.md

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Additionally, once the offline data processing is complete, users can leverage the shards stored in `output_dir` for tuning by passing it through the `--training_data_path` flag or passing it via `data_paths` argument in data config yaml, provided they find the sharded datasets beneficial for training.
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**NOTE**: The offline data preprocessing script is not compatible with processing image datasets for vision models.
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## Example Usage
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### Applying Chat Template
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pyproject.toml

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"sentencepiece>=0.1.99,<0.3",
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"tokenizers>=0.13.3,<1.0",
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"tqdm>=4.66.2,<5.0",
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"trl>=0.13,<0.17",
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"trl>=0.13,<0.18",
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"peft>=0.8.0,<0.14",
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"protobuf>=5.28.0,<6.0.0",
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"datasets>=2.15.0,<4.0",

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