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update README (#40)
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README.md

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@@ -23,9 +23,13 @@ FastFold provides a **high-performance implementation of Evoformer** with the fo
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You will need Python 3.8 or later and [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 11.1 or above when you are installing from source.
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```shell
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git clone https://github.com/hpcaitech/FastFold
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cd FastFold
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```
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We highly recommend installing an Anaconda or Miniconda environment and install PyTorch with conda:
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```
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```shell
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conda env create --name=fastfold -f environment.yml
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conda activate fastfold
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bash scripts/patch_openmm.sh
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You can get the FastFold source and install it with setuptools:
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```shell
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git clone https://github.com/hpcaitech/FastFold
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cd FastFold
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python setup.py install
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```
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init_dap(args.dap_size)
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```
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### Download the dataset
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You can down the dataset used to train FastFold by the script `download_all_data.sh`:
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./scripts/download_all_data.sh data/
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### Inference
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You can use FastFold with `inject_fastnn`. This will replace the evoformer from OpenFold with the high performance evoformer from FastFold.

environment.yml

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- typing-extensions==3.10.0.2
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- einops
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- colossalai
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- pytorch::pytorch=1.11.0
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- --find-links https://download.pytorch.org/whl/cu113/torch_stable.html torch==1.11.1+cu113
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- --find-links https://download.pytorch.org/whl/cu113/torch_stable.html torchaudio==0.11.1+cu113
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- --find-links https://download.pytorch.org/whl/cu113/torch_stable.html torchvision==0.13.1
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- conda-forge::python=3.8
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- conda-forge::setuptools=59.5.0
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- conda-forge::pip

requirements.txt

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--find-links https://download.pytorch.org/whl/cu113/torch_stable.html
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torch==1.12.1+cu113
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torchaudio==0.12.1+cu113
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torchvision==0.13.1
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einops
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colossalai
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colossalai==0.1.8

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