| --- |
| language: |
| - en |
| library_name: pytorch |
| tags: |
| - robotics |
| - robot-learning |
| - imitation-learning |
| - embodied-ai |
| - world-model |
| - vision-language-action |
| - libero |
| - robotwin |
| --- |
| |
| # Enfold Checkpoints |
|
|
| This repository provides the official checkpoints for **Enfold: Folding World-Generator Computation into Predictive Representations for Efficient Embodied Control** |
|
|
| ## What is included |
|
|
| Each benchmark has one policy checkpoint and one matching normalization-statistics file. Always use a checkpoint with the statistics file from the same row. |
|
|
| | Benchmark | Policy checkpoint | Normalization statistics | Evaluation setup | |
| | --- | --- | --- | --- | |
| | LIBERO | `enfold_libero.pt` | `libero_dataset_stats.pt` | Two camera views, concatenated to 224 × 448; 7-D actions and 8-D proprioception | |
| | RoboTwin | `enfold_robotwin.pt` | `robotwin_dataset_stats.pt` | Three camera views at 384 × 320; 14-D actions and proprioception | |
|
|
| ## Download |
|
|
| Install the Hub client, then download only the files for the benchmark you plan to evaluate: |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="richardxyt/Enfold", |
| local_dir="checkpoints/enfold_libero", |
| allow_patterns=["enfold_libero.pt", "libero_dataset_stats.pt"], |
| ) |
| ``` |
|
|
| For RoboTwin, replace the two filenames with `enfold_robotwin.pt` and `robotwin_dataset_stats.pt`. |
|
|
| ## Evaluation |
|
|
| First install the Enfold source code and its dependencies, then configure the required external model assets (Cosmos-Predict2.5, Cosmos tokenizer/VAE and text-encoder assets, DINOv3 ViT-H/16+). The source configuration contains paths that must be changed for your machine. |
|
|
| From the Enfold project root, evaluate the matching checkpoint/statistics pair: |
|
|
| ```bash |
| # LIBERO |
| bash eval.sh libero \ |
| checkpoints/enfold_libero/enfold_libero.pt \ |
| checkpoints/enfold_libero/libero_dataset_stats.pt |
| |
| # RoboTwin |
| bash eval.sh robotwin \ |
| checkpoints/enfold_robotwin/enfold_robotwin.pt \ |
| checkpoints/enfold_robotwin/robotwin_dataset_stats.pt |
| ``` |
|
|
| See the Enfold source repository for environment setup, dataset preparation, optional Hydra overrides, multi-GPU evaluation. |
|
|
| ## Citation |
|
|
| If these checkpoints help your research, please cite the model repository: |
|
|
| ```bibtex |
| @software{enfold2026, |
| title = {Enfold: Robotics Policy Checkpoints}, |
| author = {Enfold Authors}, |
| year = {2026}, |
| url = {https://huggingface.co/richardxyt/Enfold} |
| } |
| ``` |
|
|
