| --- |
| library_name: pytorch |
| tags: |
| - robotics |
| - imitation-learning |
| - diffusion-policy |
| - libero |
| --- |
| |
| # StreamingWAM LIBERO checkpoint |
|
|
| This repository contains the released StreamingWAM checkpoint trained on the |
| four standard LIBERO suites and evaluated on LIBERO-Plus. The checkpoint is |
| intended for use with the accompanying |
| [StreamingWAM code](https://github.com/renshaojie233/StreamingWAM). |
|
|
| ## File |
|
|
| | File | Size | SHA-256 | |
| | --- | ---: | --- | |
| | `streamingwam_libero.pt` | 12,042,077,420 bytes | `35499c8b2ac7bc879c988c9af4f9e9ff9052caccd22d582b7fadd90de185d496` | |
|
|
| The PyTorch checkpoint contains the model weights (`mot` and |
| `proprio_encoder`) and minimal loading metadata (`step` and `torch_dtype`). It |
| does not contain optimizer state, scheduler state, random-number-generator |
| state, training logs, or experiment-tracking data. |
|
|
| ## Usage |
|
|
| Download `streamingwam_libero.pt`, install the StreamingWAM codebase, and pass |
| the local checkpoint path to the evaluation command: |
|
|
| ```bash |
| python experiments/libero/eval_libero_task_list_multi_k.py \ |
| task=streamingwam_libero_plus \ |
| ckpt=/path/to/streamingwam_libero.pt \ |
| EVALUATION.dataset_stats_path=assets/libero_dataset_stats.json \ |
| +EVALUATION.task_list_file=assets/libero_plus_full_10030.txt \ |
| +EVALUATION.sdp_k_values='[4]' |
| ``` |
|
|
| See the code repository for the complete environment, data layout, and |
| evaluation options. |
|
|
| ## Scope and terms |
|
|
| This checkpoint is released for research on robot learning and policy |
| evaluation. The source code is MIT-licensed. External datasets, pretrained |
| components, benchmark assets, and model weights retain their respective |
| licenses and terms. |
|
|
|
|
