README.md

---
license: apache-2.0
size_categories:
- 10K<n<100K
pretty_name: ForgeWM Training Data
tags:
- world-model
- minecraft
- video-diffusion
- action-conditioned
task_categories:
- image-to-video
---

# ForgeWM Training Data

Pre-encoded latents for training [ForgeWM](https://github.com/asdfo123/ForgeWM) ([arXiv:2608.14022](https://arxiv.org/abs/2608.14022)).

Project Page: [https://asdfo123.github.io/ForgeWM/](https://asdfo123.github.io/ForgeWM/)

This is a **re-packaging** of the [GameFactory](https://github.com/KlingAIResearch/GameFactory) 
GF-Minecraft dataset, encoded into Wan2.1 VAE latents and sharded as LMDB for 
direct use by ForgeWM training scripts. The underlying gameplay videos are 
from GameFactory — we just made them training-ready.

## Quick Start

```bash
huggingface-cli download ForgeWM/ForgeWM-data \
  --local-dir ./data/action_lmdb --repo-type dataset
```

Then point ForgeWM configs to `./data/action_lmdb`.

## What's Inside

| Field | Value |
|---|---|
| Clips | 4000*10 = 40000|
| Shards | 10 LMDB files |
| Latent shape | `(21, 16, 44, 80)` — Wan2.1 VAE, 84 frames @ 352×640 decoded |
| Keyboard | one-hot W/S/A/D |
| Mouse | `[yaw, pitch]`, normalized |
| Total size | ~89 GB |

**Processing note**: GameFactory's pitch convention (`+pitch = look-down`) is 
flipped to MG2's (`mouse[0] > 0 = look-up`) at encoding time.

## Citation

```bibtex
@misc{li2026forgewm,
  title         = {ForgeWM: Progressive Causal Training for Few-Step
                   Action-Conditioned Video World Models},
  author        = {Xinye Li and Lingshuai Lin and Lei Wang and Liuzhou Zhang and
                   Jialin Cui and Qingshan Li and Guanchu Wang and Qingbin Liu and
                   Xi Chen and Jiang Bian and Wai Lam},
  year          = {2026},
  eprint        = {2608.14022},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CV},
  url           = {https://arxiv.org/abs/2608.14022}
}
```

Please also cite **GameFactory** (the underlying data):
```bibtex
@misc{yu2024gamefactory,
      title={GameFactory: Creating New Games with Generative Interactive Videos}, 
      author={Yu, Jiwen and Qin, Yiran and Wang, Xintao and Wan, Pengfei and Zhang, Di and Liu, Xihui},
      year={2025},
      eprint={2501.08325},
      archivePrefix={arXiv},
}
```

## License

Apache 2.0 for this repackaging. The underlying GF-Minecraft data follows 
[GameFactory's license](https://github.com/KlingAIResearch/GameFactory) — 
please consult their terms before redistribution.