mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
github-actions[bot]
4e9b09c222
|
1 year ago | |
---|---|---|
.. | ||
FastFold@eba496808a | 1 year ago | |
README.md | 2 years ago |
README.md
FastFold Inference
Table of contents
📚 Overview
This example lets you to try out the inference of FastFold.
🚀 Quick Start
- Install FastFold
We highly recommend you to install FastFold with conda.
git clone https://github.com/hpcaitech/FastFold
cd FastFold
conda env create --name=fastfold -f environment.yml
conda activate fastfold
python setup.py install
- Download datasets.
It may take ~900GB space to keep datasets.
./scripts/download_all_data.sh data/
- Run the inference scripts.
bash inference.sh
You can find predictions under the outputs
dir.
🔍 Dive into FastFold
There are another features of FastFold, such as:
- more excellent kernel based on triton
- much faster data processing based on ray
- training supported
More detailed information can be seen here.