RAIN v0.1.0 — pretrained models

Pretrained RAIN models for eight ManiSkill tasks, used by the public code at https://github.com/rain-policy/RAIN.

• rain-models-v0.1.0.tar.gz: 32 portable model/configuration files for eight tasks. SHA-256: 0304986672ca52b43ca170316e36886b39126ac577f64af694fba8c9afe114ff.
• rain-maniskill-source-fb3328d.tar.gz: the retained reference ManiSkill source, with upstream licenses and asset notices. SHA-256: 75350b7cab59c60369a32910485c3d612f92339d5f09be8c67145da575af8e87.
• RAIN-MODELS-LICENSE.txt: MIT license for the original RAIN model weights.

The original model and simulator archives are unchanged. Model path metadata is sanitized; all 3,104 serialized tensors and numeric routing parameters match the archived originals. Each task passed a one-episode GPU integration check against its corresponding archived episode. Full retraining and the 800-episode experiment were not repeated during packaging.

Use the current repository or the v0.1.1 code release, then run python tools/download_models.py. Downloads require no GitHub login. Installation, evaluation and training guides are linked in the README.

Project page: https://rain-policy.github.io/

Original RAIN code, documentation and these eight-task model weights use MIT. The separate ManiSkill source, simulator assets and demonstration datasets retain their upstream terms.

Paper: arXiv:2610.19765 · PDF.