← Sinan Lab › Recipe › SmolVLA
Recipe · Hugging Face (LeRobot)

SmolVLA

venv lerobot2.0 GBModel page →

Commands and version pins exactly as executed for our measurements. Replace <hardware> with the card id (rtx-4090 / rtx-5090 / a800-80g). Common steps (mirrors, disk, nohup) are on the recipes index.

1 · Environment

transformers bundled with lerobot · torch >= 2.7(独立 venv) · lerobot[smolvla]

python -m venv /root/envs/lerobot && /root/envs/lerobot/bin/pip install -U pip
/root/envs/lerobot/bin/pip install "lerobot[smolvla]"

2 · Weights

export HF_ENDPOINT=https://hf-mirror.com HF_HOME=/root/autodl-tmp/hf HF_HUB_DISABLE_XET=1
python -c "from huggingface_hub import snapshot_download as s; s('lerobot/smolvla_base')"
python -c "from huggingface_hub import snapshot_download as s; s('HuggingFaceTB/SmolVLM2-500M-Video-Instruct')"

{T.run}

{r.run}
{r['load_' + L] &&
{T.load} · {r['load_' + L]}
}

{T.pit}

{(r.pitfalls || []).map((p: any) => ())}
{T.sym}{T.fix}
{p[L]}{p['fix_' + L]}

{T.meas}

{T.src}

{rows.length ?
{rows.map((x) => ())}
{T.hwc}{T.prec}{T.p50}{T.p95}{T.vram}{T.n}{T.date}
{x.h.name}{x.prec}{fmtMs(x.p50)}{fmtMs(x.p95)}{x.vram != null ? x.vram + ' GB' : '—'}{x.n}{x.date}
:
{T.nomeas}
}
}
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