---
license: mit
library_name: pytorch
tags:
  - robotics
  - imitation-learning
  - world-model
  - image-editing
  - flux
  - imagewam
  - libero
datasets:
  - yuanty/LIBERO-fastwam
---

# ImageWAM-FLUX.2-9B-LIBERO

This repository contains the **ImageWAM FLUX.2 9B checkpoint for LIBERO** from **ImageWAM: Do World Action Models Really Need Video Generation, or Just Image Editing?**

ImageWAM is a family of world action models built on image-editing foundation models. This checkpoint is intended for evaluation and research use with the accompanying ImageWAM codebase.

## Model Details

- **Model family:** ImageWAM
- **Image-editing backbone:** FLUX.2 [klein] base
- **Variant:** FLUX.2 klein-base-9B
- **Benchmark:** LIBERO
- **Training code:** [yuyangalin/ImageWAM](https://github.com/yuyangalin/ImageWAM)
- **Base model weights:** Users must separately prepare the FLUX.2 klein-base-9B weights and FLUX.2 autoencoder as described in the ImageWAM README.

## Files

Expected file layout:

```text
.
├── model.pt
├── dataset_stats.json
└── config.yaml
```

- `model.pt`: ImageWAM checkpoint used by the evaluation scripts.
- `dataset_stats.json`: normalization statistics required for policy evaluation.
- `config.yaml`: original training configuration for provenance and reproducibility.

## Usage

Install and prepare the ImageWAM repository following the project README. Then download this model repository:

```bash
mkdir -p checkpoints/imagewam_release/libero/flux2_klein_9b

huggingface-cli download yuyangalin/ImageWAM-FLUX.2-9B-LIBERO \
  --repo-type model \
  --local-dir checkpoints/imagewam_release/libero/flux2_klein_9b
```

Prepare FLUX.2 9B weights and set:

```bash
export FLUX2_VARIANT=9b
export FLUX2_MODEL_PATH=/path/to/flux-2-klein-base-9b.safetensors
export FLUX2_AE_MODEL_PATH=/path/to/ae.safetensors
export FLUX2_QWEN3_MODEL_SPEC=Qwen/Qwen3-8B
```

Evaluate on LIBERO:

```bash
export CKPT_PATH="$(pwd)/checkpoints/imagewam_release/libero/flux2_klein_9b/model.pt"
export DATASET_STATS_PATH="$(pwd)/checkpoints/imagewam_release/libero/flux2_klein_9b/dataset_stats.json"

NUM_GPUS=8 FLUX2_VARIANT=9b bash scripts/flux2/run_eval_flux2_libero.sh
```

## Intended Use

This checkpoint is intended for:

- Reproducing ImageWAM LIBERO evaluations.
- Research on robot policy learning, world action models, and image-editing-based action generation.
- Comparison against other LIBERO policy models under the same evaluation setup.

This checkpoint is not intended for safety-critical or real-world robot deployment without additional validation.

## Limitations

- Evaluation requires the ImageWAM codebase and the LIBERO benchmark environment.
- The checkpoint assumes the same model variant and configuration used during training. See `train_config.yaml`.
- Users must separately prepare the matching FLUX.2 9B base model and autoencoder weights.
- Performance may differ if the simulator version, dataset preprocessing, action normalization statistics, or evaluation settings differ from the release setup.
- The 9B variant has higher GPU memory requirements than the 4B variant.

## Citation

If you use this checkpoint, please cite the ImageWAM paper:

```bibtex
@misc{zhang2026imagewam,
      title={ImageWAM: Do World Action Models Really Need Video Generation, or Just Image Editing?}, 
      author={Yuyang Zhang and Wenyao Zhang and Zekun Qi and He Zhang and Haitao Lin and Jingbo Zhang and Yao Mu and Xiaokang Yang and Wenjun Zeng and Xin Jin},
      year={2026},
      eprint={2606.19531},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2606.19531}, 
}
```

## Acknowledgements

ImageWAM builds on several open-source projects and model families, including FLUX.2, FastWAM, LIBERO, LIBERO-plus, and RoboTwin. Please also follow the licenses and citation requirements of the corresponding upstream projects.