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.
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:
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.