JAM — LIBERO checkpoints
The three original LIBERO paper checkpoints of JAM, one folder per backbone. Each folder is a self-contained package with its checkpoint, normalization statistics, configuration, recorded results, pinned dependencies and release.py.
Project · Code · arXiv:2610.37219 · Hugging Face paper
| Policy | Folder | Checkpoint |
|---|---|---|
| JAM (Wan) | libero/wan |
12.18 GB |
| JAM (Ovis-U1) | libero/ovis-u1 |
4.37 GB |
| JAM (Qwen3.5-2B) | libero/qwen3.5-2b |
7.25 GB |
Recorded results
LIBERO: 40 tasks × 50 episodes = 2,000 episodes. LIBERO-Plus: the paper's fixed 1,506-task subset, one episode per task, seed 42; AVG is task-weighted. These are the original single-training-seed results; per-task counts are in each folder's results/.
LIBERO
| Policy | Spatial | Object | Goal | Long | AVG |
|---|---|---|---|---|---|
| JAM (Wan) | 98.80 | 100.00 | 98.00 | 95.80 | 98.15 |
| JAM (Ovis-U1) | 98.60 | 99.60 | 98.40 | 90.40 | 96.75 |
| JAM (Qwen3.5-2B) | 97.80 | 99.60 | 97.20 | 91.60 | 96.55 |
LIBERO-Plus
| Policy | Spatial | Object | Goal | Long | AVG |
|---|---|---|---|---|---|
| JAM (Wan) | 74.24 | 67.20 | 57.84 | 59.52 | 64.54 |
| JAM (Ovis-U1) | 82.27 | 86.24 | 78.15 | 73.28 | 79.95 |
| JAM (Qwen3.5-2B) | 84.76 | 88.10 | 75.84 | 76.19 | 81.14 |
Download one policy
Resolve the revision once and download one folder of that immutable snapshot:
from huggingface_hub import HfApi, snapshot_download
repo = "y0urOy/JAM"
revision = HfApi().model_info(repo).sha
snapshot_download(repo, revision=revision, allow_patterns="libero/wan/*", local_dir="./jam")
print(revision) # retain with your experiment
Use libero/ovis-u1/* or libero/qwen3.5-2b/* for the other policies.
Then run python jam/libero/wan/release.py verify and follow that folder's README.md to install the matching environment and evaluate. These policies are loaded by JAM's load_checkpoint, not AutoModel.from_pretrained.
License
Weights retain the Apache-2.0 terms of their base models; see each folder's LICENSE and notice files.
Citation
@article{yu2026jam,
title={Vision-Language-Action or World-Action? Just Action Models},
author={Yonghao Yu and Lang Huang and Runyi Li and Toshihiko Yamasaki},
journal={arXiv preprint arXiv:2610.37219},
year={2026},
url={https://arxiv.org/abs/2610.37219}
}