Psi Quick Start
April 27, 2026 ยท View on GitHub
This guide assumes a fresh clone of the public repo at
https://github.com/physical-superintelligence-lab/Psi0.
The baseline quick starts under this directory use the xmove-pick SIMPLE dataset:
third_party/SIMPLE/data/G1WholebodyXMoveAndPickMP-v0
Unless noted otherwise, commands assume you are already inside the top-level
Psi0 dev shell started from the repo root with nix develop.
1. Clone and initialize the repo
git clone git@github.com:physical-superintelligence-lab/Psi0.git Psi0
cd Psi0
git submodule update --init --recursive
If your Git setup blocks local file transport for submodules, use:
git -c protocol.file.allow=always submodule update --init --recursive
Pull Git LFS content inside SIMPLE:
cd third_party/SIMPLE
git submodule foreach --recursive 'git lfs install --local || true'
git submodule foreach --recursive 'git lfs pull || true'
cd ../..
2. Enter the repo dev shell
cd /path/to/Psi0
env -u LD_LIBRARY_PATH nix --extra-experimental-features "nix-command flakes" develop
This shell composes the PSI and SIMPLE runtime.
3. Create the repo Python environment
From the repo root:
uv venv .venv-psi --python 3.10
source .venv-psi/bin/activate
GIT_LFS_SKIP_SMUDGE=1 uv sync --all-groups --index-strategy unsafe-best-match --active
cp .env.sample .env
The repo-level uv sync installs psi and simple as editable packages.
4. Prepare baseline-specific environments
H-RDT:
cd /path/to/Psi0/src/h_rdt
uv sync --frozen
EgoVLA:
cd /path/to/Psi0/src/egovla
uv sync --frozen
GR00T-N1.6
cd /path/to/Psi0/src/gr00t
uv sync --frozen
5. Download required assets
The baseline guides below use:
- Dataset:
third_party/SIMPLE/data/G1WholebodyXMoveAndPickMP-v0 - H-RDT release weights downloaded under
src/h_rdt - EgoVLA base checkpoint downloaded under
src/egovla/checkpoints
Download the H-RDT release weights:
cd /path/to/Psi0/src/h_rdt
huggingface-cli download --resume-download embodiedfoundation/H-RDT --local-dir ./
This download provides the DINO-SigLIP files under bak/dino-siglip and the
pretrained backbone under checkpoints/pretrain-0618/.../pytorch_model.bin.
Download the EgoVLA base checkpoint:
cd /path/to/Psi0/src/egovla
source .venv/bin/activate
huggingface-cli download rchal97/egovla_base_vlm --repo-type model --local-dir checkpoints
That download currently provides a zip file. Extract it and link it to the
path expected by finetune.sh:
cd /path/to/Psi0/src/egovla/checkpoints
unzip -q vila-qwen2-vl-1.5b-instruct-sft-20240830191953.zip
ln -sfn \
vila-qwen2-vl-1.5b-instruct-sft-20240830191953 \
mix4data-30hz-transv2update2-fingertip-20e-hdof5-3d200-rot5-lr1e-4-h5p30f1skip6-b16-4
Related Guides
gr00t.mdhrdt.mdegovla.mdsimple.md