diff --git a/.github/workflows/gh-pages.yaml b/.github/workflows/gh-pages.yaml
new file mode 100644
index 0000000..0e4e038
--- /dev/null
+++ b/.github/workflows/gh-pages.yaml
@@ -0,0 +1,48 @@
+name: Deploy Documentation to GitHub Pages
+
+on:
+  push:
+    branches:
+      - main
+    
+  pull_request:
+    branches:
+      - main
+
+permissions:
+  contents: write
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v3
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.9'
+
+    - name: Set up Pandoc
+      run: |
+        sudo apt-get update
+        sudo apt-get install -y pandoc
+
+    - name: Install dependencies
+      run: |
+        pip install sphinx sphinx-autodoc-typehints sphinx_book_theme sphinx-copybutton
+        pip install nbsphinx recommonmark Pygments
+        pip install pandoc
+
+    - name: Build the docs
+      run: |
+        cd docs
+        make html
+
+    - name: Deploy to GitHub Pages
+      uses: peaceiris/actions-gh-pages@v3
+      with:
+        github_token: ${{ secrets.GITHUB_TOKEN }}
+        publish_dir: ./docs/_build/html
\ No newline at end of file
diff --git a/.nojekyll b/.nojekyll
new file mode 100644
index 0000000..e69de29
diff --git a/docs/Makefile b/docs/Makefile
new file mode 100644
index 0000000..d4bb2cb
--- /dev/null
+++ b/docs/Makefile
@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = .
+BUILDDIR      = _build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
diff --git a/docs/README.md b/docs/README.md
new file mode 100644
index 0000000..f9911d2
--- /dev/null
+++ b/docs/README.md
@@ -0,0 +1,30 @@
+# MatterSim Documentations
+
+## Prerequisite
+To compile the documentations on your local machine you will need to install
+the following dependency in your environment:
+```bash
+# sphinx
+pip install sphinx sphinx-autodoc-typehints sphinx_book_theme sphinx-copybutton
+
+# enable Markdown documentation in sphinx
+pip install recommonmark
+
+# enable python jupyter notebook in sphinx
+pip install nbsphinx nbconvert
+
+# install pandoc
+conda install -c conda-forge pandoc
+```
+
+## Compile the docs
+Under the root of this repo, execute the following commandline
+```bash
+sphinx-build -b html docs docs/_build
+```
+To browse the documentation on your local machine, you may start a minimal
+HTTP server with
+```bash
+python3 -m http.server --directory docs/_build 8000
+```
+In a web browser, e.g. Chrome or Edge, you can read the docs at [localhost at port 8000](http://localhost:8000).
diff --git a/docs/conf.py b/docs/conf.py
new file mode 100644
index 0000000..b0036b3
--- /dev/null
+++ b/docs/conf.py
@@ -0,0 +1,48 @@
+# -*- coding: utf-8 -*-
+import os
+import sys
+
+from recommonmark.parser import CommonMarkParser  # noqa: F401
+
+sys.path.append(os.path.abspath("../src"))
+
+# -- Project information -----------------------------------------------------
+project = "MatterSim"
+copyright = "2024"
+author = "Microsoft Corporation"
+release = "1.0.0"
+
+# -- General configuration ---------------------------------------------------
+extensions = [
+    "sphinx.ext.autodoc",
+    "sphinx.ext.napoleon",
+    "sphinx_autodoc_typehints",
+    "sphinx.ext.mathjax",
+    "sphinx_copybutton",
+    "recommonmark",
+    "nbsphinx",
+]
+
+source_suffix = {
+    ".rst": "restructuredtext",
+    ".md": "markdown",
+}
+
+templates_path = ["_templates"]
+exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
+html_theme = "sphinx_book_theme"
+html_theme_options = {
+    "repository_url": "https://github.com/microsoft/mattersim",
+    "repository_provider": "github",
+    "use_repository_button": True,
+}
+
+# colorful codes
+# pygments_style = 'sphinx'  # or any other Pygments style you prefer
+# pygments_style = 'solarized-dark'  # or any other Pygments style you prefer
+
+html_static_path = ["_static"]
+
+# -- Options for nbsphinx ----------------------------------------------------
+nbsphinx_allow_errors = True
+nbsphinx_execute = "never"
diff --git a/docs/examples/examples.rst b/docs/examples/examples.rst
new file mode 100644
index 0000000..c7e3f35
--- /dev/null
+++ b/docs/examples/examples.rst
@@ -0,0 +1,9 @@
+Examples
+========
+
+.. toctree::
+   :maxdepth: 1
+   :numbered:
+
+   relax_example
+   phonon_example.ipynb
diff --git a/docs/examples/phonon_example.ipynb b/docs/examples/phonon_example.ipynb
new file mode 100644
index 0000000..ef59d2f
--- /dev/null
+++ b/docs/examples/phonon_example.ipynb
@@ -0,0 +1,246 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Phonon Dispersion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from ase.build import bulk\n",
+    "from ase.visualize import view\n",
+    "from mattersim.forcefield.potential import Potential, DeepCalculator\n",
+    "from mattersim.applications.phonon import PhononWorkflow\n",
+    "\n",
+    "%config InlineBackend.figure_format = 'retina'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Set up the atomic structure with attached MatterSim Calculator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create structure\n",
+    "si = bulk(\"Si\")\n",
+    "\n",
+    "# to visualize the structure, uncomment the following line\n",
+    "# view(si.repeat([2,2,2]), viewer=\"x3d\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create MatterSim calculator\n",
+    "potential = Potential.load(load_path=\"/path/to/checkpoint\")\n",
+    "calc = DeepCalculator(potential=potential)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# attach calculator to the structure\n",
+    "si.calc = calc"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Set up the phonon workflow"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['transformation_matrix']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['international']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['rotations']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['translations']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['number']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['wyckoffs']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['equivalent_atoms']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Supercell matrix for 2nd force constants : \n",
+      "[[2 0 0]\n",
+      " [0 2 0]\n",
+      " [0 0 2]]\n",
+      "\n",
+      "\n",
+      "Inferring forces for displaced atoms and computing fcs ...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|          | 0/1 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 1/1 [00:00<00:00,  1.19it/s]\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['std_lattice']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['std_positions']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['std_types']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['std_rotation_matrix']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max drift of force constants: 0.000003 (xx) 0.000003 (yy)\n",
+      "Max drift after symmetrization by translation: 0.000000 (zz) 0.000000 (zz)\n",
+      "Qpoints mesh for Brillouin Zone integration : [12 12 12]\n",
+      "Dispersion relations using phonopy for Si2 ...\n",
+      "\n",
+      "Has imaginary phonon: False\n",
+      "Phonon frequencies: <phonopy.api_phonopy.Phonopy object at 0x7af8347654c0>\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['uni_number']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['international']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['number']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n",
+      "/home/hanyang/miniforge3/envs/mattersim/lib/python3.9/site-packages/spglib/spglib.py:115: DeprecationWarning: dict interface (SpglibDataset['hall']) is deprecated.Use attribute interface ({self.__class__.__name__}.{key}) instead\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 394,
+       "width": 563
+      }
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 428,
+       "width": 562
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ph = PhononWorkflow(\n",
+    "    atoms=si,\n",
+    "    find_prim = False,\n",
+    "    work_dir = \"/tmp/phonon_si_example\",\n",
+    "    amplitude = 0.01,\n",
+    "    supercell_matrix = np.diag([2,2,2]),\n",
+    ")\n",
+    "has_imag, phonons = ph.run()\n",
+    "print(f\"Has imaginary phonon: {has_imag}\")\n",
+    "print(f\"Phonon frequencies: {phonons}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Si2_phonon_band.png  band.yaml\t\t  total_dos.dat\n",
+      "Si2_phonon_dos.png   phonopy_params.yaml\n"
+     ]
+    }
+   ],
+   "source": [
+    "# In the work_dir, you can find the output files of the phonon calculation,\n",
+    "# including the phonon dispersion, phonon density of states, etc.\n",
+    "!ls /tmp/phonon_si_example"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "mattersim",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/examples/relax_example.rst b/docs/examples/relax_example.rst
new file mode 100644
index 0000000..1fa77ac
--- /dev/null
+++ b/docs/examples/relax_example.rst
@@ -0,0 +1,39 @@
+Structure Optimization
+======================
+
+This is a simple example of how to perform a structure optimization using the MatterSim.
+
+Import the necessary modules
+----------------------------
+
+.. code-block:: python
+
+    import numpy as np
+    from ase.build import bulk
+    from mattersim.forcefield.potential import Potential
+    from mattersim.forcefield.potential import DeepCalculator
+
+Set up the structure to relax
+-----------------------------
+
+.. code-block:: python
+
+    # initialize the structure of silicon
+    si = bulk("Si", "diamond", a=5.43)
+
+    # perturb the structure
+    si.positions += 0.1 * np.random.randn(len(si), 3)
+
+    # load the model
+    potential = Potential.load(load_path="/path/to/checkpoint", device="cuda:0")
+
+    # create a calculator from the model
+    calculator = DeepCalculator(potential=potential)
+
+    # attach the calculator to the atoms object
+    si.calc = calculator
+
+Create the optimizer
+--------------------
+
+MatterSim implements a built-in relaxation class to support the relaxation of ase atoms.
diff --git a/docs/index.rst b/docs/index.rst
new file mode 100644
index 0000000..be4b4a7
--- /dev/null
+++ b/docs/index.rst
@@ -0,0 +1,76 @@
+.. mattersim documentation master file, created by
+   sphinx-quickstart on Thu Aug 22 14:01:40 2024.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+Welcome to the MatterSim Documentation!
+=======================================
+
+Overview
+--------
+
+`MatterSim <https://arxiv.org/abs/2405.04967>`_ is an advanced deep learning model designed to simulate 
+the properties of materials across a wide range of elements, temperatures, and pressures. 
+The model leverages state-of-the-art deep learning techniques to deliver high accuracy and 
+efficiency in atomistic simulations, making it a valuable tool for researchers 
+in the field of materials science.
+
+MatterSim is still in active development, and more checkpoints may be
+released in appropriate time, so please stay tuned for updates.
+
+Pre-trained Models
+------------------
+
+We currently offer two pre-trained versions of MatterSim with **M3GNet** architecture:
+
+1. **mattersim-mini-v1.0.0**: A mini version of the model that is faster to run. 
+2. **mattersim-medium-v1.0.0**: A medium version of the model that is more accurate.
+
+These models have been trained using the data generated through the workflows 
+introduced in the `MatterSim <https://arxiv.org/abs/2405.04967>`_ manuscript, which provides an in-depth 
+explanation of the methodologies underlying the MatterSim model.
+
+FAQ
+---
+
+**Q1**: What is the difference between the mini and medium versions of MatterSim?
+
+   **A**: The mini version is a smaller model that is faster to run, while the medium version is more accurate.
+
+**Q2**: Are you going to release the pre-trained models of MatterSim with transformer-based architectures?
+
+   **A**: The transformer-based MatterSim is still under development. Please contact us for more information.
+
+Bibliography
+------------
+
+.. note::
+
+   If you use MatterSim in your research, please cite the following paper:
+
+   .. code-block:: bibtex
+
+      @article{yang2024mattersim,
+         title={
+            Mattersim: A deep learning atomistic model across elements,
+            temperatures and pressures
+         },
+         author={
+            Yang, Han and Hu, Chenxi and Zhou, Yichi and Liu, Xixian
+            and Shi, Yu and Li, Jielan and Li, Guanzhi and Chen, Zekun
+            and Chen, Shuizhou and Zeni, Claudio and others
+         },
+         journal={arXiv preprint arXiv:2405.04967},
+         year={2024}
+      }
+
+
+
+.. toctree::
+   :maxdepth: 2
+   :caption: User Guide:
+   :hidden:
+
+   user_guide/installation
+   user_guide/getting_started
+   examples/examples
diff --git a/docs/make.bat b/docs/make.bat
new file mode 100644
index 0000000..32bb245
--- /dev/null
+++ b/docs/make.bat
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+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=.
+set BUILDDIR=_build
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.https://www.sphinx-doc.org/
+	exit /b 1
+)
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd
diff --git a/docs/user_guide/getting_started.rst b/docs/user_guide/getting_started.rst
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+Getting Started
+===============
+
+A minimal example
+-----------------
+
+The following example demonstrates how to load a pre-trained potential and make predictions for a single structure.
+
+.. code-block:: python
+    :linenos:
+
+    from ase.build import bulk
+    from mattersim.forcefield.potential import Potential
+    from mattersim.datasets.utils.build import build_dataloader
+
+    # set up the structure
+    si = bulk("Si", "diamond", a=5.43)
+
+    # load the model
+    potential = Potential.load(load_path="/path/to/checkpoint", device="cuda:0")
+
+    # build the dataloader that is compatible with MatterSim
+    dataloader = build_dataloader([si], only_inference=True, model_type=model_name)
+
+    # make predictions
+    predictions = potential.predict_properties(dataloader, include_forces=True, include_stresses=True)
+
+    # print the predictions
+    print(f"Total energy in eV: {predictions[0]}")
+    print(f"Forces in eV/Angstrom: {predictions[1]}")
+    print(f"Stresses in GPa: {predictions[2]}")
+
+
+Interface to ASE
+----------------
+
+MatterSim provides an interface to the Atomic Simulation Environment (ASE) to facilitate the use of MatterSim potentials in the popular ASE package.
+
+.. code-block:: python
+    :linenos:
+
+    from ase.build import bulk
+    from mattersim.forcefield.potential import DeepCalculator
+
+    # same as before
+    si = bulk("Si", "diamond", a=5.43)
+    potential = Potential.load(load_path="/path/to/checkpoint", device="cuda:0")
+
+    # set up the calculator
+    calculator = DeepCalculator(
+        potential=potential,
+        # important! convert GPa to eV/Angstrom^3
+        stress_weight=1 / 160.21766208,
+    )
+
+    si.calc = calculator
+    # or
+    si.set_calculator(calculator)
+
+    print(si.get_potential_energy())
+    print(si.get_forces())
+    print(si.get_stress(voigt=False))
+
+
+In the example above, the `DeepCalculator` class implements the ASE calculator interface. The **stress_weight** parameter is used to convert the stress tensor from GPa to :math:`\mathrm{eV}\cdot\mathrm{\mathring{A}}^{-3}`.
+
+.. warning ::
+    By default, the ASE package assumes :math:`\mathrm{eV}\cdot\mathrm{\mathring{A}}^{-3}` for the stress tensor. However, MatterSim uses GPa for the stress tensor. Therefore, the **stress_weight** parameter is necessary to convert the stress tensor from GPa to :math:`\mathrm{eV}\cdot\mathrm{\mathring{A}}^{-3}`.
diff --git a/docs/user_guide/installation.rst b/docs/user_guide/installation.rst
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+
+Installation
+============
+
+Install from PyPI
+-----------------
+
+TODO: To be released to PyPI.
+
+
+Install from source code
+------------------------
+
+Requirements:
+
+* Python == 3.9
+* PyTorch == 1.11.0
+
+To install the package, run the following command under the root of the folder:
+
+.. code-block:: console
+
+    conda env create -f environment.yaml
+    conda activate mattersim
+    pip install -e .
+
+Obtain the model checkpoints
+----------------------------
+
+You may obtain our model checkpoints from
+
+.. code-block:: console
+
+    # link to somewhere