| --- |
| license: apache-2.0 |
| base_model: Wan-AI/Wan2.2-TI2V-5B |
| pipeline_tag: image-to-video |
| library_name: eawm |
| tags: |
| - robotics |
| - world-model |
| - video-generation |
| - wan2.2 |
| - lora |
| --- |
| |
| # EA-WM |
|
|
| Official final checkpoint for **EA-WM: Event-Aware Generative World Model with Structured Kinematic-to-Visual Action Fields**. |
|
|
| - Paper: https://arxiv.org/abs/2605.06192 |
| - Code and documentation: https://github.com/Shownx-c/EA-WM |
| - Base model: https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B |
|
|
| ## Model |
|
|
| Given an initial RGB frame and a text instruction, EA-WM jointly generates future RGB and KVAF videos through event-aware bidirectional fusion. |
|
|
| ## Checkpoint |
|
|
| | File | Contents | Use | |
| |:--|:--|:--| |
| | `final.safetensors` | RGB-stream LoRA, KVAF-stream LoRA, KVAF prediction head, and event-aware bidirectional fusion | Inference and evaluation | |
|
|
| The checkpoint contains EA-WM adapters and auxiliary branch weights. Download the Wan2.2-TI2V-5B base model separately. Follow the repository README to install the code, prepare the base model, and run inference. |
|
|
| ## Download |
|
|
| ```bash |
| hf download shown21/EA-WM final.safetensors --local-dir weights |
| ``` |
|
|
| ## Inference |
|
|
| From the EA-WM code directory, create a task list using [`configs/inference_tasks.example.json`](https://github.com/Shownx-c/EA-WM/blob/main/configs/inference_tasks.example.json), then run: |
|
|
| ```bash |
| export CHECKPOINT=weights/final.safetensors |
| export TASK_JSON=configs/inference_tasks.example.json |
| export OUTPUT_ROOT=outputs/inference/joint_generation |
| |
| bash scripts/infer.sh |
| ``` |
|
|
| RGB videos are saved in `videos/` and jointly generated KVAF videos in `kvaf_videos/` under `OUTPUT_ROOT`. |
|
|
| ## Checkpoint metadata |
|
|
| The checkpoint uses the public EA-WM parameter names, LoRA rank `32`, and fusion interval `5`. File integrity can be checked against `SHA256SUMS`. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{yang2026eawm, |
| title = {EA-WM: Event-Aware Generative World Model with Structured Kinematic-to-Visual Action Fields}, |
| author = {Yang, Zhaoyang and Jin, Yurun and Qi, Lizhe and Chen, Kai and Huang, Cong}, |
| journal = {arXiv preprint arXiv:2605.06192}, |
| year = {2026} |
| } |
| ``` |
|
|
| ## License |
|
|
| The EA-WM code and released checkpoint are provided under Apache-2.0. Use of the Wan2.2 base model and datasets remains subject to their respective terms. |
|
|
