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code/cosmos/ # clone of NVIDIA/cosmos (cookbooks) + output/ (this
# project's scripts, LoRA adapters, generated videos,
# logs, analysis for physics/reasoning experiments)
code/cosmos-framework/ # unmodified clone of NVIDIA/cosmos-framework (training
# framework dependency, used via nvidia/Cosmos3-Nano)
experiments/ # working directories referenced by code/cosmos/output/*
# scripts (LoRA checkpoints, precompute caches, generated
# samples for each experiment: bon*, gate1*, m1_*,
# stage1_*, stage2_*, s2_*, ttr3*_*, emph*, overflow*,
# rollout_held4*)
env/ # pip freeze / uv pip freeze for the two envs used
# (cosmos3: python3.13 uv venv, cosmos-fw: python3.13 uv venv)nvidia/Cosmos3-Nano base model weights: loaded via from_pretrained
directly from the Hugging Face Hub at runtime, not stored locally.ckpt/videocon_physics (14GB) and vjepa2_ckpt/vitl.pt (4.8GB):
publicly downloadable evaluator/encoder checkpoints (VideoCon-Physics,
VJEPA2 ViT-L), same artifacts used in the companion VideoREPA project.physicsiq/ (20GB): the public
Physics-IQ benchmark
dataset, used read-only for evaluation — not re-hosted here.env/requirements_cosmos3.txt and env/requirements_cosmos-fw.txt are captured
via pip freeze / uv pip freeze from the two uv-managed Python 3.13 venvs used
for this project. Recreate with:1uv venv --python 3.13 .venv-cosmos3 && uv pip install -r env/requirements_cosmos3.txt
2uv venv --python 3.13 .venv-cosmos-fw && uv pip install -r env/requirements_cosmos-fw.txtcode/cosmos-framework's own pyproject.toml / uv.lock is the authoritative
dependency spec for that framework; the requirements dump above is a snapshot of
what was actually installed.