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DeePMD-kit Logo
v2.2.6

Getting Started

  • Getting Started
    • 1. Easy install
    • 2. DeePMD-kit Quick Start Tutorial

Advanced

  • 1. Installation
  • 2. Data
  • 3. Model
  • 4. Training
  • 5. Freeze and Compress
  • 6. Test
  • 7. Inference
  • 8. Command line interface
  • 9. Integrate with third-party packages
  • 10. Use NVNMD
  • 11. FAQs

Tutorial

  • Tutorials
  • Publications

Developer Guide

  • Find DeePMD-kit C/C++ library from CMake
  • Create a model
  • Atom Type Embedding
  • Coding Conventions
  • CI/CD
  • Python API
  • OP API
  • C++ API
  • C API
  • Core API

Project Details

  • License
  • Authors and Credits
  • Logo
DeePMD-kit
  • Getting Started
  • Edit on GitHub

Getting Started

In this text, we will call the deep neural network that is used to represent the interatomic interactions (Deep Potential) the model. The typical procedure of using DeePMD-kit is

  • 1. Easy install
    • 1.1. Install off-line packages
    • 1.2. Install with conda
    • 1.3. Install with docker
    • 1.4. Install Python interface with pip
  • 2. DeePMD-kit Quick Start Tutorial
    • 2.1. Task
    • 2.2. Table of contents
    • 2.3. Get tutorial data via git
    • 2.4. General Introduction
    • 2.5. Data preparation
    • 2.6. Prepare input script
    • 2.7. Train a model
    • 2.8. Freeze a model
    • 2.9. Test a model
    • 2.10. Run MD with LAMMPS
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