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---
pretty_name: TeleArms raw demonstrations (three tasks)
tags:
- robotics
extra_gated_prompt: Access is granted manually to collaborators of the TeleArms project.
---
# TeleArms raw demonstrations: three tasks
Raw human teleoperation demonstrations of a simulated bimanual YAM robot (MuJoCo), recorded in
the TeleArms game. Every demo here succeeded and passed the acceptance checks of the TeleArms v5
training dataset; this repo holds all of that dataset's human demos of three tasks:
- Red Cube In Front Of Blue Cube: 6,109 demos
- L Cube Arrangement: 11,990 demos
- Three Cube Pyramid Stacking: 2,547 demos
20,646 demos, 246 GB, in 50 tar shards.
## Files
`data/<task>/<task>-NNN.tar` holds `<task>/<uuid>/` per demo:
- `<uuid>.safetensors` (played in the cloud) or `<uuid>.safetensors.gz` (played in the browser,
gzip-compressed): the recorded robot and object states (`info_qpos`, `info_qvel`) and the
commanded actions (`info_demo_action`) at 500 Hz, with metadata (environment name, seed,
package versions; for browser play also the start layout `reset_layout`).
- `<uuid>.json`: the game's record of the attempt (task, duration, success, metrics).
- `verification.json` (browser play only): the server's replay check of the demo.
`manifest.csv` lists every demo with its task, where it was played (`cloud` or `local` =
browser) and its shard.
## Loading
The trajectories are read and replayed with the `roboeval` package of the TeleArms code base:
`Demo.from_safetensors(path)` reads both file types (a gzipped file must keep its `.gz` suffix).
A browser-play demo replays only after its `reset_layout` is applied on top of the seeded reset;
the seed alone does not reproduce its start layout.