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Running on Zero
Running on Zero
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# Human-maintained direct dependencies (top-level).
# Use `uv` to compile this into a fully pinned `requirements.txt` lockfile.
#
# IMPORTANT:
# - We intentionally do NOT list `torch` here because the Docker image base
# (`nvcr.io/nvidia/pytorch`) already provides it. Installing torch via pip
# during image build is slow and can lead to ABI/CUDA mismatches.
# - If you are NOT using Docker, install an appropriate PyTorch build separately.
#
# Config / wiring
hydra-core>=1.3
omegaconf>=2.3
# Core numerics
numpy>=1.23,<2
scipy>=1.10,<2
# Model / embeddings
# NOTE: `kimodo/model/llm2vec` is has only been tested with transformers==5.1.0
transformers==5.1.0
urllib3>=2.6.3
boto3
peft>=0.12
einops>=0.7
# Misc
tqdm>=4.0
packaging>=21.0
pydantic>=2.0
# UI / client
filelock>=3.20.3
gradio>=6.8.0
gradio_client>=1.0
# Visualization
trimesh>=3.21.7
scenepic>=1.1.0
pillow>=9.0
av>=16.1.0
py-soma-x @ git+https://github.com/NVlabs/SOMA-X.git
# Local packages (editable installs for viser and kimodo; MotionCorrection non-editable)
./MotionCorrection
-e .
viser @ git+https://github.com/nv-tlabs/kimodo-viser.git
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