metadata
license: mit
tags:
- reinforcement-learning
- embodied-ai
- behavior-cloning
- crafter
- craftax
- video-language
CrafterDojo v1 weights
Pretrained models from CrafterDojo: An Integrated Research Suite for Building Open-Ended Embodied Agents in Crafter (paper, code, project).
| File | Model | Notes |
|---|---|---|
vpt/tiny.safetensors |
CrafterVPT-tiny | behavior cloning, last checkpoint |
vpt/base.safetensors |
CrafterVPT-base | behavior cloning, last checkpoint |
vpt/large.safetensors |
CrafterVPT-large | behavior cloning, last checkpoint |
crafterclip/crafterclip.safetensors |
CrafterCLIP | video–caption encoder (MineCLIP architecture, ViT-B/16 backbone) |
steve1/steve1.safetensors |
CrafterSteve-1 | instruction-following policy (LoRA on CrafterVPT-base) |
steve1/steve1_prior.safetensors |
CrafterSteve-1 prior | text → visual-goal CVAE prior |
vpt/*.yaml |
architecture configs | same files as models/vpt/*.yaml in the code repository |
All models are trained on the sv_gh_pp-10B_20ep CrafterPlay mixture (Survival + Gatherer experts) in Craftax-Classic.
Each .safetensors file records its training run in the header metadata.
Usage
git clone https://github.com/frechele/CrafterDojo && cd CrafterDojo
bash scripts/download_weights.sh # downloads this repository (revision v1.0) into models/
Load with the repository's helpers (crafterdojo.common.checkpoint.load_state_dict), which also restore the
shared CLIP tensors in CrafterCLIP (stored once, listed in the aliases metadata entry).
Citation
@article{park2026crafterdojo,
title = {CrafterDojo: An Integrated Research Suite for Building Open-Ended Embodied Agents in Crafter},
author = {Park, Junyeong and Cho, Hyeonseo and Ahn, Sungjin},
journal = {arXiv preprint arXiv:2508.13530},
year = {2026}
}