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xming521
7daa270736
Integrate suffixed encrypted storage across extraction, review, training, and inference. Add shared-password web authentication with two-hour sessions, private request logging, and an isolated profile-building pipeline. Fix encrypted dataset discovery at training entrypoints and duplicate CSV imports. Add synthetic storage, authentication, and log checks; update documentation and frontend assets.
21 lines
597 B
Python
21 lines
597 B
Python
from llamafactory.hparams import get_infer_args
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from llamafactory.train.tuner import export_model
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from weclone.train.security import model_runtime, parsed_cli_arguments
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from weclone.utils.secure_storage import is_encrypted_mode
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def main():
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if not is_encrypted_mode():
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export_model()
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return
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config = parsed_cli_arguments(get_infer_args)
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if config.get("export_hub_model_id"):
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raise ValueError("Encrypted model export requires a local export_dir")
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with model_runtime(config) as runtime:
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export_model(runtime)
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if __name__ == "__main__":
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main()
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