license: other
tags:
- robotics
- world-model
- robotwin
- multi-view
- pytorch
Multi-WAM World v6 migration bundle
This public repository is a reproducible transfer bundle for the current Multi-WAM RoboTwin2.0
World Model v6 stage. The 2026-08-05 update adds the complete modified v6 source, frozen
Qwen3-VL-2B runtime, the audited World step-80000 migration checkpoint, migration inputs, deployment
evidence, and an agent Skill. Unchanged, SHA-identical archives from the previous release are reused:
the packed mira conda environment, codec step-125000, LingBot/Wan runtime assets, and the complete
27,500-episode latent/text cache.
The raw RoboTwin2.0 dataset is intentionally not included. Download or mount the 100 ALOHA ZIP
files separately at datasets/RoboTwin2.0; World v6 needs their original three-view RGB frames when
building Qwen anchors.
Current restore set
| Archive | Restores | Status |
|---|---|---|
source-code-world-v6-20260805.tar.zst |
current mira/, lingbot-vision/, v6 plans |
new |
mira-conda-env.tar.zst |
relocatable Python 3.12 / Torch 2.8 CUDA 12.8 environment | reused |
runtime-models.tar.zst |
LingBot-Vision Large and Wan UMT5 assets | reused |
qwen3-vl-2b-instruct.tar.zst |
pinned frozen Qwen3-VL-2B current encoder | new |
codec-checkpoint-step125000.tar.zst |
codec weights plus optimizer/training state | reused |
world-checkpoint-step80000.tar.zst |
complete 32-shard audited v5 World migration source | new |
world-derived-cache.tar.zst |
complete latent/text cache and generated metadata | reused |
world-v6-migration-inputs.tar.zst |
EMA selection, state encoder, smoke reports/videos | new |
Historical source, World-50k, and individually uploaded World-80k objects remain in repository history for compatibility, but the current restore script does not download or extract them.
All current payloads are covered by SHA256SUMS. Exact source/archive sizes, hashes, model contracts,
and reused/new status are recorded in PACKAGE_MANIFEST.json. No credential is included.
Direct selective download
Install a recent Hugging Face CLI, clear every proxy, and download only the current restore set:
unset http_proxy https_proxy all_proxy ftp_proxy HTTP_PROXY HTTPS_PROXY ALL_PROXY FTP_PROXY
export NO_PROXY='*' no_proxy='*' HF_XET_HIGH_PERFORMANCE=1
hf download Orangerl/multi-wam \
--include README.md PACKAGE_MANIFEST.json SHA256SUMS 'skills/**' \
archives/source-code-world-v6-20260805.tar.zst \
archives/mira-conda-env.tar.zst \
archives/runtime-models.tar.zst \
archives/qwen3-vl-2b-instruct.tar.zst \
archives/codec-checkpoint-step125000.tar.zst \
archives/world-checkpoint-step80000.tar.zst \
archives/world-derived-cache.tar.zst \
archives/world-v6-migration-inputs.tar.zst \
--local-dir multi-wam-hf
Then ask an agent to use skills/multi-wam-migrate/SKILL.md. The deterministic restore entry point
is:
bash skills/multi-wam-migrate/scripts/restore_bundle.sh \
"$PWD" /path/to/Mutil_WAM /path/to/conda/envs/mira
After downloading/mounting the ALOHA data and creating a destination-local SwanLab token, run
verify_install.sh and start_world_v6_smoke.sh. The smoke launcher uses only physical GPUs 6 and
7. Formal World v6 remains an explicitly guarded eight-GPU pipeline.
Official dataset: https://huggingface.co/datasets/TianxingChen/RoboTwin2.0
Official RoboTwin code: https://github.com/RoboTwin-Platform/RoboTwin
MIRA and LingBot-Vision retain their upstream Apache-2.0 notices. Bundled third-party model assets, checkpoints, and conda packages retain their respective licenses, so this aggregate repository uses the mixed/other label rather than relicensing its contents.