tao-convert-dataset-format
Run `tao-daft convert` to convert NVIDIA TAO DAFT datasets between supported formats. Do not use for non-DAFT data. Use when the user asks to convert a DAFT dataset, change DAFT format, change a TAO dataset format, or run `tao-daft convert`.
npx skills add NVIDIA/skills --skill tao-convert-dataset-format --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Convert a TAO DAFT Dataset ## Quick start ```bash tao-daft convert <source-format> <target-format> --path <input> --output <output> ``` Source and target are positional subcommands; `--path` and `--output` are flags. Discover the supported formats and per-pair flags from the leaf `--help` (see "CLI conventions" below). ## Preflight ```bash python -c "import nvidia_tao_daft" 2>/dev/null || { echo
What does the tao-convert-dataset-format skill do?
Run `tao-daft convert` to convert NVIDIA TAO DAFT datasets between supported formats. Do not use for non-DAFT data. Use when the user asks to convert a DAFT dataset, change DAFT format, change a TAO dataset format, or run `tao-daft convert`.
How do I install it?
Run `npx skills add NVIDIA/skills --skill tao-convert-dataset-format --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From NVIDIA/skills, a repository with 2,789 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
