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LeRobot now supports full language annotations

Brief

LeRobot released full language support for its dataset format: lerobot-annotate points a vision-language model at each episode and produces subtasks, plans, memory entries, and grounded Q&A (~$1.20 per 100 episodes). Recipes then turn those annotations into policy-agnostic training messages so the same dataset can be reused to train planning, memory, tool invocation, or low-level control models; details are on the Hugging Face blog.

Why it matters

LeRobot now supports full language annotations: lerobot-annotate uses a vision-language model to generate subtasks, plans, episodic memory, and grounded Q&A for each episode.

Key details

  • Annotation cost is about $1.20 per 100 episodes; annotated rows are converted by recipes into policy-agnostic training messages that can teach planning, memory, tool calls, or low-level control without redesigning the dataset.
Source evidence

Most robot datasets store one sentence per episode: the task. Real problems need more: a plan, a memory, room to answer questions and change course.

We just shipped full language support in the LeRobot dataset format. Now lerobot-annotate points a vision-language model at each episode and writes the subtasks, plans, memory, and grounded Q&A itself - roughly $1.20 for 100 episodes.

From there, recipes turn the annotated rows into policy-agnostic training messages, so the same dataset can teach planning, memory, tool calls, or low-level control, no dataset redesign required.

Read how it all works on the blog: huggingface.co/spaces/lerobo…

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