---
license: cc-by-nc-4.0
library_name: easywam
base_model: Wan-AI/Wan2.2-TI2V-5B
tags:
  - robotics
  - world-action-model
  - imitation-learning
  - libero
  - wan2.2
  - lora
---

# EasyWAM-Hidden-Wan22-LoRA-128

EasyWAM-Hidden conditions a separate Action DiT on intermediate features from a Wan2.2 Video DiT. This checkpoint was trained on LIBERO using rank-128 LoRA (`r=128`, `alpha=128`) with Wan2.2-TI2V-5B as the backbone.

The corresponding checkpoint was obtained by training with the [EasyWAM](https://github.com/OpenMOSS/EasyWAM) codebase.

## Results

Success rate (%) under the EasyWAM LIBERO evaluation protocol:

| Model | Spatial | Object | Goal | Long | Avg. |
| --- | :---: | :---: | :---: | :---: | :---: |
| **Full-Parameter** | | | | | |
| EasyWAM-Unified | 99.0 | 99.4 | 99.2 | 98.2 | 99.0 |
| EasyWAM-MoT | 97.8 | 98.4 | 97.6 | 95.6 | 97.4 |
| EasyWAM-Hidden | 99.4 | 100.0 | 97.0 | 97.8 | 98.6 |
| **LoRA (Rank 128)** | | | | | |
| EasyWAM-Unified | 84.0 | 97.8 | 92.0 | 81.2 | 88.8 |
| EasyWAM-MoT | 96.8 | 98.8 | 94.4 | 90.4 | 95.1 |
| 🔥 EasyWAM-Hidden | 96.8 | 99.4 | 92.6 | 86.8 | 93.9 |

Success rate (%) under the LIBERO-Plus evaluation protocol:

| Model | Background | Camera | Language | Layout | Light | Noise | Robot | Avg. |
| --- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
| EasyWAM-Unified | 55.8 | 33.7 | 93.7 | 80.6 | 92.2 | 50.2 | 71.4 | 67.5 |
| EasyWAM-MoT | 52.8 | 20.6 | 80.4 | 65.2 | 85.1 | 51.5 | 49.7 | 56.8 |
| EasyWAM-Hidden | 56.8 | 49.2 | 95.3 | 81.0 | 90.4 | 58.2 | 77.4 | 72.4 |


## Download

```bash
hf download OpenMOSS-Team/EasyWAM-Hidden-Wan22-LoRA-128 \
  easywam_hidden_wan22_lora_128.pt \
  --local-dir ./checkpoints
```

## Evaluation

Prepare Wan2.2, LIBERO, and the matching `dataset_stats.json` as described in the [EasyWAM LIBERO guide](https://github.com/OpenMOSS/EasyWAM/blob/main/docs/libero.md), then run:

```bash
python experiments/libero/run_libero_manager.py \
  task=libero_easywam_hidden_wan22_lora \
  ckpt=./checkpoints/easywam_hidden_wan22_lora_128.pt
```

EasyWAM creates the matching LoRA modules from the task config and merges them for evaluation when loading this checkpoint.

## Checkpoint Details

- Architecture: EasyWAM-Hidden
- Backbone: Wan2.2-TI2V-5B
- Training: LoRA, rank 128, alpha 128
- Dataset: LIBERO, two cameras at 224 px
- Training steps: 20,000
- Action dimension: 7
- State dimension: 8
- Format: EasyWAM PyTorch checkpoint (`.pt`)

## License and Citation

EasyWAM code is released under the MIT License. Use of this checkpoint is also subject to the terms of its base model and training data. See the [EasyWAM repository](https://github.com/OpenMOSS/EasyWAM) for citation information.