Minecraft World Model — Checkpoints
Autoregressive video world model for Minecraft. A frozen Stable Diffusion VAE compresses 256×256 frames to 4×32×32 latents; a decoder-only transformer (338M params, RoPE, DWS-style per-block action adapters, SDPA flash attention) predicts the next latent conditioned on discrete action tokens (29 ids: 22 keyboard + 6 camera bins + 1 no-op).
- Data:
TESS-Computer/minecraft-vla-stage1(streaming parquet, 303 shards) - Code & training: https://github.com/keypaa/minecraft-world-jepa
- Precision: bfloat16. Normalization: disabled (checkpoints carry no mean/std).
Layout
Each run directory holds a full resumable state (model + optimizer +
scheduler + step/epoch counters), so any file below restarts training
bit-identically with the matching config and --resume:
world-model-stage1-4ctx/
latest.pt # freshest state (≤4 min old during training)
best.pt # lowest-loss state
epoch_0000_loss_0.266776.pt
epoch_0001_loss_0.238446.pt
Stage 1 (ctx 4, batch 32) — complete
| Epoch | Loss |
|---|---|
| 1 | 0.266776 |
| 2 | 0.238446 |
Measured on RTX PRO 6000: ~1.2s/step steady, ~64GB reserved VRAM.
License note
Weights derive from public TESS-VLA gameplay data and an sd-vae-ft-mse
base. No license is asserted here — check the dataset and base-model terms
before commercial use.