---
license: mit
task_categories:
  - reinforcement-learning
tags:
  - world-models
  - control
  - trajectories
  - lance
  - stable-worldmodel
configs:
  - config_name: default
    data_files:
      - split: train
        path: viewer/*.parquet
---

# LeWM Reacher

DeepMind Control Reacher trajectories from `quentinll/lewm-reacher`, repackaged for direct inspection and streaming.

[Open in the LeWM Dataset Visualizer](https://fracapuano-lewm-dataset-visualizer.static.hf.space/?dataset=fracapuano%2Flewm-reacher&config=default&split=train)

## Data

- 10,000 episodes
- 2,010,000 timesteps
- 201 steps per episode
- 224 × 224 RGB observations

Core fields are `pixels` (RGB), `action` (float32[2]), and `observation` (float32[6]). The source diagnostics are retained: `finger_pos`, `qpos`, `qvel`, `target_pos`, `reward`, `score`, `success`, `terminated`, `truncated`, `render_time`, `id`, and `ep_idx`. `episode_idx` and `step_idx` are canonical indices.

`train.lance` is the indexed training table. `viewer/` is a Parquet mirror for the Hugging Face dataset viewer and the LeWM visualizer.

```python
from stable_worldmodel.data.formats.lance import LanceDataset

dataset = LanceDataset(
    "hf://datasets/fracapuano/lewm-reacher/train.lance",
    num_steps=16,
)
sample = dataset[0]
```

## Provenance

- Source: [`quentinll/lewm-reacher`](https://huggingface.co/datasets/quentinll/lewm-reacher)
- Source revision: `e70a080d0d04c6072123c9ebd343acf7fff28dbf`
- Source archive SHA-256: `4ff2385e49712caa89f21b8e0a246e2614b621d3f22cf2d1224d845e879a1cc2`
- Lance schema implementation: `stable-worldmodel` revision `85d325cc77449c3889e52b03ee7e561cb2fc0383`
- License: MIT

All episode boundaries and numeric fields were validated against the source after canonical float32 normalization. Across 145 sampled frames, JPEG pixel MAE averaged 0.903/255 with a maximum sample mean of 0.925/255. Another 130 rows verified the Parquet mirror against Lance, including identical JPEG bytes.

The [stable-worldmodel paper](https://arxiv.org/abs/2605.21800) reports faster local and remote trajectory loading with Lance than HDF5 on PushT.