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# FastFold Inference
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## Table of contents
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- [FastFold Inference](#fastfold-inference)
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- [Table of contents](#table-of-contents)
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- [📚 Overview](#-overview)
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- [🚀 Quick Start](#-quick-start)
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- [🔍 Dive into FastFold](#-dive-into-fastfold)
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## 📚 Overview
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This example lets you to try out the inference of [FastFold](https://github.com/hpcaitech/FastFold).
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## 🚀 Quick Start
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1. Install FastFold
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We highly recommend you to install FastFold with conda.
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```
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git clone https://github.com/hpcaitech/FastFold
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cd FastFold
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conda env create --name=fastfold -f environment.yml
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conda activate fastfold
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python setup.py install
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```
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2. Download datasets.
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It may take ~900GB space to keep datasets.
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```
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./scripts/download_all_data.sh data/
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```
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3. Run the inference scripts.
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```
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bash inference.sh
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```
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You can find predictions under the `outputs` dir.
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## 🔍 Dive into FastFold
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There are another features of [FastFold](https://github.com/hpcaitech/FastFold), such as:
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+ more excellent kernel based on triton
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+ much faster data processing based on ray
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+ training supported
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More detailed information can be seen [here](https://github.com/hpcaitech/FastFold/).
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