rfdiffusion
The instruction below should work on MacOSX M1 architecture without GPU support, so it will be slooooww…
git clone https://github.com/RosettaCommons/RFdiffusion.git
cd RFdiffusion
mkdir models && cd models
wget http://files.ipd.uw.edu/pub/RFdiffusion/6f5902ac237024bdd0c176cb93063dc4/Base_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/e29311f6f1bf1af907f9ef9f44b8328b/Complex_base_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/60f09a193fb5e5ccdc4980417708dbab/Complex_Fold_base_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/74f51cfb8b440f50d70878e05361d8f0/InpaintSeq_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/76d00716416567174cdb7ca96e208296/InpaintSeq_Fold_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/5532d2e1f3a4738decd58b19d633b3c3/ActiveSite_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/12fc204edeae5b57713c5ad7dcb97d39/Base_epoch8_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/f572d396fae9206628714fb2ce00f72e/Complex_beta_ckpt.pt
wget http://files.ipd.uw.edu/pub/RFdiffusion/1befcb9b28e2f778f53d47f18b7597fa/RF_structure_prediction_weights.pt
Download the following into ./env
https://github.com/YaoYinYing/RFdiffusion/blob/mps-test/env/SE3nv_macos.yml
conda env create -f ./SE3nv_macos.yml
conda activate RFdiffusion
conda install 'pytorch==2.3.0' torchvision torchaudio cpuonly -c pytorch
pip install 'dgl==2.2.1' -f https://data.dgl.ai/wheels/repo.html
pip install git+https://github.com/YaoYinYing/nvtx-mock --force-reinstall
pip install nvtx
pip install git+https://github.com/YaoYinYing/SE3Transformer@rfdiffusion-mps-test
pip install git+https://github.com/NVIDIA/dllogger#egg=dllogger
pip install git+https://github.com/YaoYinYing/RFdiffusion@mps-test
pip install pydantic
pip install torchdata==0.9.0
conda activate RFdiffusion
cd ./examples
tar -xvf ./ppi_scaffolds_subset.tar.gz
Make your first run:
./scripts/run_inference.py 'contigmap.contigs=[150-150]' inference.output_prefix=test_outputs/test inference.num_designs=10