Git LFS vs DVC — when to use each?

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$Git LFS: extends git for large files, but still one repo.$
$Small teams, few big files (models).$
$Limits: GitHub bandwidth (~1GB/mo free), full clone downloads everything.$
$DVC: git tracks metadata, data in cloud (unlimited scale); pull-what-you-need; supports data pipelines.$
$Better for actual ML at scale (100 GB + datasets).$
$Modern: DVC for data + models; git LFS for smaller ancillary files.$

Check yourself — multiple choice

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Git LFS: git for large files but one repo + bandwidth limits + full download; DVC: git tracks metadata + data in cloud + unlimited scale + pull what needed + pipelines; DVC for real ML, LFS for small ancillary
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Git LFS (small teams / few files) vs DVC (real ML scale + pipelines).

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