---
license: mit
tags:
  - robotics
  - flow-matching
  - libero
  - robotwin
---

# RoboActualizer checkpoints

Checkpoints of Roboactualizer, a joint image/action flow-matching policy on a frozen V-JEPA 2.1 ViT-L/16 encoder.
Code, environments and full instructions: the Roboactualizer repository.

| Folder | Model | Benchmark | Inference | Result | Eval config |
|---|---|---|---|---|---|
| `libero_dits/` | DiT-S, step 173580 | LIBERO (4 suites x 10 tasks x 50) | 4 steps, no CFG, bf16 | 98.00 | `eval_libero_dits` |
| `libero_dits/` | DiT-S, step 173580 | LIBERO-Plus (10,030 tasks x 1) | 4 steps, action text-CFG 1.5, bf16 | 63.1 | `eval_libero_plus_dits` |
| `libero_ditb/` | DiT-B, step 130185 | LIBERO-Plus (10,030 tasks x 1) | 4 steps, action text-CFG 1.5, bf16 | 65.0 | `eval_libero_plus_ditb` |
| `robotwin_dits_fp32/` | DiT-S, fp32 weights, step 176540 | RoboTwin 2.0 (50 tasks x clean/randomized x 25) | 10 steps, no CFG, fp32 | 58.84 | `eval_robotwin_dits` |

Each folder holds the checkpoint, the `dataset_stats.json` used for action/state normalization (keep it next to the
checkpoint; evaluation looks for it there) and the training `config.yaml`. `SHA256SUMS` lists file hashes.

All checkpoints use the 300M V-JEPA 2.1 encoder:
`https://dl.fbaipublicfiles.com/vjepa2/vjepa2_1_vitl_dist_vitG_384.pt`, saved as
`checkpoints/vjepa2/vjepa2_1_vit_large_384.pt` in the code repository.

## Usage

```bash
huggingface-cli download db12312607/RoboActualizer --exclude "data/*" --local-dir checkpoints/roboactualizer

# from the code repository root
python experiments/libero/run_libero_manager.py --config-name eval_libero_dits \
    ckpt=checkpoints/roboactualizer/libero_dits/step_173580.pt
bash experiments/libero/run_libero_plus.sh --config-name=eval_libero_plus_ditb \
    ckpt=checkpoints/roboactualizer/libero_ditb/step_130185.pt
python experiments/robotwin/run_robotwin_manager.py --config-name eval_robotwin_dits \
    ckpt=checkpoints/roboactualizer/robotwin_dits_fp32/step_176540.pt
```