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- Streaming pipeline: row-group-level parquet reading (PyArrow) so large files never fully land in RAM; Welford online algorithm for normalizer fitting; StreamingStepsDataset with shuffle buffer and multi-worker file striping; event-ID scan and vocab scan via cheap single-column reads - giant/cli.py: typer-based CLI with `giant train` subcommand, mirroring scripts/train.py; --shuffle-buffer flag for RAM control - pyproject.toml: add typer>=0.12 dependency and giant entry point - train.py: replace len(loader.dataset) with local counters (compatible with IterableDataset which has no __len__) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>