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improve hf jobs docs

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Nikodem Bartnik
2026-07-02 11:20:08 +02:00
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docs/source/hardware_guide.mdx
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@@ -82,18 +82,18 @@ VRAM is the first filter. Within a tier, pick by budget and availability — the
### Hugging Face Jobs
[Hugging Face Jobs](https://huggingface.co/docs/hub/jobs) lets you run training on managed HF infrastructure, billed by the second. The repo publishes a ready-to-use image: **`huggingface/lerobot-gpu:latest`**, rebuilt **every night at 02:00 UTC from `main`** ([`docker_publish.yml`](https://github.com/huggingface/lerobot/blob/main/.github/workflows/docker_publish.yml)) — so it tracks the current state of the repo, not a tagged release.
[Hugging Face Jobs](https://huggingface.co/docs/hub/jobs) lets you run training on managed HF infrastructure, billed by the second, without owning a GPU. `lerobot-train` submits and streams the job for you — just add `--job.target=<flavor>` to a normal training command:
```bash
hf jobs run --flavor a10g-large huggingface/lerobot-gpu:latest \
bash -c "nvidia-smi && lerobot-train \
--policy.type=act --dataset.repo_id=<USER>/<DATASET> \
--policy.repo_id=<USER>/act_<task> --batch_size=8 --steps=50000"
lerobot-train \
--policy.type=act --dataset.repo_id=<USER>/<DATASET> \
--policy.repo_id=<USER>/act_<task> \
--job.target=a10g-large
```
Notes:
- The leading `nvidia-smi` is a quick sanity check that CUDA is visible inside the container — useful to fail fast if the flavor or driver mismatched.
- The default Job timeout is 30 minutes; pass `--timeout 4h` (or longer) for real training.
- `--flavor` maps onto the table above: `t4-small`/`t4-medium` (T4, ACT only), `l4x1`/`l4x4` (L4 24 GB), `a10g-small/large/largex2/largex4` (A10G 24 GB scaled out), `a100-large` (A100). For the current full catalogue + pricing see [https://huggingface.co/docs/hub/jobs](https://huggingface.co/docs/hub/jobs).
- Prefer not to write the `hf jobs run` wrapper yourself? `lerobot-train` can submit the job for you: just add `--job.target=<flavor>` to a normal training command and it handles dataset upload, log streaming, and the final model push. See the [imitation-learning training guide](./il_robots).
- Run `hf auth login` once before submitting, the job runs under your token.
- `--job.target` maps onto the table above: `t4-small`/`t4-medium` (T4, ACT only), `l4x1`/`l4x4` (L4 24 GB), `a10g-small/large/largex2/largex4` (A10G 24 GB scaled out), `a100-large` (A100). List the current catalogue with pricing via `hf jobs hardware`, or see [https://huggingface.co/docs/hub/jobs](https://huggingface.co/docs/hub/jobs).
- The job defaults to a `2d` (48h) timeout; override it with `--job.timeout=4h` (or any other duration string) to fail faster or run longer.
- For the full walkthrough — dataset upload, checkpoint streaming, resuming a run on a job — see the [imitation-learning training guide](./il_robots#train-using-hugging-face-jobs).