diff --git a/.github/actions/install/action.yml b/.github/actions/install/action.yml
index 349a06d1a..10f48bcb1 100644
--- a/.github/actions/install/action.yml
+++ b/.github/actions/install/action.yml
@@ -18,7 +18,7 @@ inputs:
     description: "The requirements file depends on the hardware, i.e., CPU, GPU, or macOS"
     required: true
     default: "cpu"
-    options: ["cpu", "gpu", "macos"]
+    options: ["cpu", "cu118", "cu121", "macos"]
 
 runs:
   using: "composite"
diff --git a/.gitignore b/.gitignore
index 8d75ef473..d8d702060 100644
--- a/.gitignore
+++ b/.gitignore
@@ -130,9 +130,10 @@ dmypy.json
 
 # Documentation
 docs/build/html
-docs/**/*.rst
+docs/source/api/*.rst
 docs/source/*.md
 
+
 # Badges
 assets/badges
 
diff --git a/docs/parse_about.py b/docs/parse_about.py
deleted file mode 100644
index 94e09b7d4..000000000
--- a/docs/parse_about.py
+++ /dev/null
@@ -1,110 +0,0 @@
-"""Script to parse paper.md file to About section for website."""
-
-import argparse
-import re
-
-
-def main(input_file: str, output_file: str) -> None:
-    """Parsing script."""
-    # Check(s)
-    assert input_file != output_file
-    assert input_file.endswith(".md")
-    assert output_file.endswith(".md")
-
-    # Read input file contents
-    with open(input_file, "r") as f:
-        content = f.read()
-
-    # Get all section headers and constituent paragraphs
-    sections = list(re.finditer("^# (.*?)\n", content, re.M))
-    corpus = {}
-    for s1, s2 in zip(sections[:-1], sections[1:]):
-        corpus[s1.group(1)] = [
-            par for par in content[s1.end() : s2.start()].split("\n") if par
-        ]
-
-    # Stitch together an About section
-    content = "\n\n".join(
-        [
-            "# About",
-            corpus["Summary"][1],
-            "## Impact",
-        ]
-        + corpus["Impact on physics"]
-        + [
-            "## Usage",
-        ]
-        + corpus["Usage"][:1]
-        + ["### FIGURE ###"]
-        + corpus["Usage"][2:]
-        + [
-            "## Acknowledgements",
-            "### EU EMBLEM ###",
-        ]
-        + corpus["Acknowledgements"]
-    )
-
-    # Add figure
-    figure = corpus["Usage"][1]
-    m = re.search(
-        r"!\[(?P<caption>.*) *\\label\{.*\} *\]\((?P<path>.*)\)", figure, re.M
-    )
-    caption, path = m.group("caption"), m.group("path")
-    content = content.replace(
-        "### FIGURE ###",
-        f"""
-:::{{figure-md}} flowchart
-:class: figclass
-
-<img src="../../paper/{path.replace(".pdf", ".png")}" alt="flowchart" width="100%">
-
-{caption}
-:::""",
-    )
-
-    # Remove references
-    pattern = "\[[@\:\w]+\]"
-    references = re.findall(pattern, content)
-    for reference in references:
-        content = content.replace(f" {reference}", "")
-
-    # Update figure reference
-    content = content.replace(
-        "\\autoref{fig:flowchart}", "[the Figure](flowchart)"
-    )
-
-    # Update acknowledgements to include EU emblem.
-    content = content.replace(
-        "Andreas Søgaard has received", "This project has received"
-    )
-    content = content.replace(
-        "### EU EMBLEM ###",
-        f"""
-:::{{figure-md}} eu-emblem
-
-<img src="../../assets/images/eu-emblem.jpg" alt="eu-emblem" width="10 ex">
-
-&nbsp;
-:::"""
-    )
-
-    # Write parsed results to output file
-    with open(output_file, "w") as f:
-        f.write(content)
-
-
-if __name__ == "__main__":
-
-    # Parse command-line arguments
-    parser = argparse.ArgumentParser(
-        description="""
-Parse paper.md file to About section for website.
-"""
-    )
-
-    parser.add_argument("-i", "--input-file", required=True)
-    parser.add_argument("-o", "--output-file", required=True)
-
-    args = parser.parse_args()
-
-    main(args.input_file, args.output_file)
diff --git a/docs/parse_contributing.py b/docs/parse_contributing.py
deleted file mode 100644
index 577f3de76..000000000
--- a/docs/parse_contributing.py
+++ /dev/null
@@ -1,53 +0,0 @@
-"""Script to parse CONTRIBUTING.md file to contrib instructions for website."""
-
-import argparse
-import re
-
-
-def main(input_file: str, output_file: str) -> None:
-    """Parsing script."""
-    # Check(s)
-    assert input_file != output_file
-    assert input_file.endswith(".md")
-    assert output_file.endswith(".md")
-
-    # Read input file contents
-    with open(input_file, "r") as f:
-        content = f.read()
-
-    # Remove "Version control"-section everything after it.
-    pattern = "## Version control"
-    m = re.search(pattern, content)
-    content = content[: m.start()]
-
-    # Trim for whitespaces and newlines
-    content = content.strip()
-
-    # Rename title
-    content = "\n".join(["# Contribute"] + content.split("\n")[1:])
-
-    # Update relative links for absolute ones
-    content = content.replace(
-        "./", "../../"
-    )
-
-    # Write parsed results to output file
-    with open(output_file, "w") as f:
-        f.write(content)
-
-
-if __name__ == "__main__":
-
-    # Parse command-line arguments
-    parser = argparse.ArgumentParser(
-        description="""
-Parse CONTRIBUTING.md file to contrib instructions for website.
-"""
-    )
-
-    parser.add_argument("-i", "--input-file", required=True)
-    parser.add_argument("-o", "--output-file", required=True)
-
-    args = parser.parse_args()
-
-    main(args.input_file, args.output_file)
diff --git a/docs/parse_install.py b/docs/parse_install.py
deleted file mode 100644
index 8dd428d62..000000000
--- a/docs/parse_install.py
+++ /dev/null
@@ -1,61 +0,0 @@
-"""Script to parse README.md file to installation instructions for website."""
-
-import argparse
-import re
-
-
-def main(input_file: str, output_file: str) -> None:
-    """Parsing script."""
-    # Check(s)
-    assert input_file != output_file
-    assert input_file.endswith(".md")
-    assert output_file.endswith(".md")
-
-    # Read input file contents
-    with open(input_file, "r") as f:
-        content = f.read()
-
-    # Remove anything before "Install" section
-    pattern = r"^##.* Install.*$\n"
-    m = re.search(pattern, content, re.M)
-    content = "\n".join(["# Install", content[m.end() :]])
-
-    # Remove everying after "Install"
-    pattern = r"##.*$"
-    m = next(re.finditer(pattern, content, re.M))
-    content = content[: m.start()]
-
-    # Convert relevant <details>-blocks to headers
-    pattern = (
-        r"<details>\n" r"<summary><b>(.*?)<\/b><\/summary>\n" r"<blockquote>"
-    )
-    for m in re.finditer(pattern, content, re.M):
-        content = content.replace(m.group(0), "## " + m.group(1))
-
-    content = content.replace("</blockquote>\n</details>", "")
-
-    # Trim for whitespaces and newlines
-    content = content.strip()
-    for _ in range(2):
-        content = content.replace("\n\n\n", "\n\n")
-
-    # Write parsed results to output file
-    with open(output_file, "w") as f:
-        f.write(content)
-
-
-if __name__ == "__main__":
-
-    # Parse command-line arguments
-    parser = argparse.ArgumentParser(
-        description="""
-Parse README.md file to installation instructions for website.
-"""
-    )
-
-    parser.add_argument("-i", "--input-file", required=True)
-    parser.add_argument("-o", "--output-file", required=True)
-
-    args = parser.parse_args()
-
-    main(args.input_file, args.output_file)
diff --git a/docs/source/about/about.rst b/docs/source/about/about.rst
new file mode 100644
index 000000000..8ac10fdbe
--- /dev/null
+++ b/docs/source/about/about.rst
@@ -0,0 +1,37 @@
+.. include:: ../substitutions.rst
+
+About
+============
+
+|graphnet|\ GraphNeT is an open-source Python framework aimed at providing high quality, user friendly, end-to-end functionality to perform reconstruction tasks at neutrino telescopes using deep learning. |graphnet|\ GraphNeT makes it fast and easy to train complex models that can provide event reconstruction with state-of-the-art performance, for arbitrary detector configurations, with inference times that are orders of magnitude faster than traditional reconstruction techniques.
+|graphnet|\ GraphNeT provides a common, detector agnostic framework for ML developers and physicists that wish to use the state-of-the-art tools in their research. By uniting both user groups, |graphnet|\ GraphNeT aims to increase the longevity and usability of individual code contributions from ML developers by building a general, reusable software package based on software engineering best practices, and lowers the technical threshold for physicists that wish to use the most performant tools for their scientific problems.
+
+Usage
+-----
+
+|graphnet|\ GraphNeT comprises a number of modules providing the necessary tools to build workflows from ingesting raw training data in domain-specific formats to deploying trained models in domain-specific reconstruction chains, as illustrated in [the Figure](flowchart).
+
+.. _flowchart:
+.. figure:: ../../../paper/flowchart.png
+
+    High-level overview of a typical workflow using |graphnet|\ GraphNeT: :code:`graphnet.data` enables converting domain-specific data to industry-standard, intermediate file formats and reading this data; :code:`graphnet.models` allows for configuring and building complex models using simple, physics-oriented components; :code:`graphnet.training` manages model training and experiment logging; and finally, :code:`graphnet.deployment` allows for using trained models for inference in domain-specific reconstruction chains.
+
+:code:`graphnet.models` provides modular components subclassing :code:`torch.nn.Module`, meaning that users only need to import a few existing, purpose-built components and chain them together to form a complete model. ML developers can contribute to |graphnet|\ GraphNeT by extending this suite of model components — through new layer types, physics tasks, graph connectivities, etc. — and experiment with optimising these for different reconstruction tasks using experiment tracking.
+
+These models are trained using :code:`graphnet.training` on data prepared using :code:`graphnet.data`, to satisfy the high I/O loads required when training ML models on large batches of events, which domain-specific neutrino physics data formats typically do not allow.
+
+Trained models are deployed to a domain-specific reconstruction chain, yielding predictions, using the components in :code:`graphnet.deployment`. This can either be through model files or container images, making deployment as portable and dependency-free as possible.
+
+By splitting up the model development as in :numref:`flowchart`, |graphnet|\ GraphNeT allows physics users to interface only with high-level building blocks or pre-trained models that can be used directly in their reconstruction chains, while allowing ML developers to continuously improve and expand the framework’s capabilities.
+
+
+Acknowledgements
+----------------
+
+
+.. image:: ../../../assets/images/eu-emblem.jpg
+    :width: 150
+
+This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 890778.
+
+The work of Rasmus Ørsøe was partly performed in the framework of the PUNCH4NFDI consortium supported by DFG fund "NFDI 39/1", Germany.
\ No newline at end of file
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 22c1da88d..da4f76e08 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -46,6 +46,9 @@
     "myst_parser",
 ]
 
+# Figure references
+numfig = True
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]
 
diff --git a/docs/source/contribute/contribute.rst b/docs/source/contribute/contribute.rst
new file mode 100644
index 000000000..70ac9492f
--- /dev/null
+++ b/docs/source/contribute/contribute.rst
@@ -0,0 +1,54 @@
+.. include:: ../substitutions.rst
+
+Contributing To GraphNeT\ |graphnet-header|
+===========================================
+To make sure that the process of contributing is as smooth and effective as possible, we provide a few guidelines in this contributing guide that we encourage contributors to follow.
+
+GitHub issues
+-------------
+
+Use `GitHub issues <https://github.com/graphnet-team/graphnet/issues>`_ for tracking and discussing requests and bugs. If there is anything you'd wish to contribute, the best place to start is to create a new issues and describe what you would like to work on. Alternatively you can assign open issues to yourself, to indicate that you would like to take ownership of a particular task. Using issues actively in this way ensures transparency and agreement on priorities. This helps avoid situations with a lot of development effort going into a feature that e.g. turns out to be outside of scope for the project; or a specific solution to a problem that could have been better solved differently.
+
+Pull requests
+-------------
+
+Develop code in a fork of the `main repo <https://github.com/graphnet-team/graphnet>`_. Make contributions in dedicated development/feature branches on your forked repositories, e.g. if you are implementing a specific :code:`GraphDefinition` class you could create a branch named :code:`add-euclidean-graph-definition` on your own fork.
+
+Create pull requests from your development branch into :code:`graphnet-team/graphnet:main` to contribute to the project. **To be accepted,** pull requests must:
+
+* pass all automated checks,
+
+* be reviewed by at least one other contributor. These reviews should check for:
+
+  #. standard python coding conventions, e.g. `PEP8 <https://www.python.org/dev/peps/pep-0008/>`_
+
+  #. docstring (Google-style) and type hinting as necessary
+
+  #. unit tests as necessary
+
+  #. clean coding practices, see e.g. `here <https://gist.github.com/wojteklu/73c6914cc446146b8b533c0988cf8d29>`_. 
+
+Conventions
+-----------
+
+This repository aims to support python 3 version that are actively supported (currently :code:`>=3.8`). Standard python coding conventions should be followed:
+
+* Adhere to `PEP8 <https://www.python.org/dev/peps/pep-0008/>`_  `black <https://black.readthedocs.io/>`_
+* Use `pylint <https://www.pylint.org/>`_ / `flake8 <https://flake8.pycqa.org/>`_ and `black <https://black.readthedocs.io/>`_ to ensure as clean and well-formatted code as possible
+* When relevant, adhere to `clean code practices <https://gist.github.com/wojteklu/73c6914cc446146b8b533c0988cf8d29>`_
+
+Code quality
+------------
+
+To ensure consistency in code style and adherence to select best practices, we **require** that all developers use :code:`black`, :code:`flake8`, :code:`mypy`, :code:`pydocstyle`, and :code:`docformatter` for automatically formatting and checking their code. This can conveniently be done using pre-commit hooks. To set this up, first make sure that you have installed the :code:`pre-commit` python package. It is included when installing |graphnet|\ GraphNeT with the :code:`develop` tag, i.e., :code:`pip install -e .[develop]`. Then, do
+
+.. code-block:: bash
+   
+   pre-commit install
+
+
+Then, everytime you commit a change, your code and docstrings will automatically be formatted using :code:`black` and :code:`docformatter`, while :code:`flake8`, :code:`mypy`, and :code:`pydocstyle` will check for errors and adherence to PEP8, PEP257, and static typing. See an illustration of the concept below:
+
+.. image:: ../../../assets/images/precommit_pipeline.png
+
+Image source: https://ljvmiranda921.github.io/notebook/2018/06/21/precommits-using-black-and-flake8/
\ No newline at end of file
diff --git a/docs/source/index.rst b/docs/source/index.rst
index da9a39a0e..388886f5e 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -5,6 +5,9 @@
    :maxdepth: 1
    :hidden:
 
-   install
-   contribute
-   api/graphnet.rst
\ No newline at end of file
+   
+   installation/install.rst
+   api/graphnet.rst
+   about/about.rst
+   contribute/contribute.rst
+   
\ No newline at end of file
diff --git a/docs/source/installation/install.rst b/docs/source/installation/install.rst
new file mode 100644
index 000000000..ff08f2371
--- /dev/null
+++ b/docs/source/installation/install.rst
@@ -0,0 +1,46 @@
+.. include:: ../substitutions.rst
+
+Installation
+============
+
+|graphnet|\ GraphNeT is available for Python 3.8 to Python 3.11.
+
+.. note::
+   We recommend installing |graphnet|\ GraphNeT in a separate environment, e.g. using a Python virtual environment or Anaconda (see details on installation `here <https://www.anaconda.com/products/individual>`_).
+
+Quick Start
+-----------
+
+.. raw:: html
+   :file: quick-start.html
+
+
+When installation is completed, you should be able to run `the examples <https://github.com/graphnet-team/graphnet/tree/main/examples>`_.
+
+Installation in CVMFS (IceCube)
+-------------------------------
+
+You may want |graphnet|\ GraphNeT to be able to interface with IceTray, e.g., when converting I3 files to a deep learning friendly file format, or when deploying models as part of an IceTray chain. In these cases, you need to install |graphnet|\ GraphNeT in a Python runtime that has IceTray installed.
+
+To achieve this, we recommend installing |graphnet|\ GraphNeT into a CVMFS with IceTray installed, like so:
+
+.. code-block:: bash
+   
+   # Download GraphNeT
+   git clone https://github.com/graphnet-team/graphnet.git
+   cd graphnet
+   # Open your favorite CVMFS distribution
+   eval `/cvmfs/icecube.opensciencegrid.org/py3-v4.2.1/setup.sh`
+   /cvmfs/icecube.opensciencegrid.org/py3-v4.2.1/RHEL_7_x86_64/metaprojects/icetray/v1.5.1/env-shell.sh
+   # Update central utils
+   pip install --upgrade pip>=20
+   pip install wheel setuptools==59.5.0
+   # Install graphnet into the CVMFS as a user
+   pip install --user -r requirements/torch_cpu.txt -e .[torch, develop]
+
+
+Once installed, |graphnet|\ GraphNeT is available whenever you open the CVMFS locally.
+
+.. note::
+   We recommend installing |graphnet|\ GraphNeT without GPU in clean metaprojects.
+
diff --git a/docs/source/installation/quick-start.html b/docs/source/installation/quick-start.html
new file mode 100644
index 000000000..4850e029a
--- /dev/null
+++ b/docs/source/installation/quick-start.html
@@ -0,0 +1,139 @@
+<style>
+  .quick-start {
+    display: flex;
+    flex-direction: row;
+    flex-wrap: nowrap;
+    margin-bottom: 20px;
+  }
+
+  .title-column {
+    flex-grow: 0;
+  }
+
+  .content-column {
+    flex-grow: 1;
+  }
+
+  .row {
+    display: flex;
+    flex-direction: row;
+    flex-wrap: nowrap;
+  }
+
+  .title-column div, .row div {
+    white-space: nowrap;
+  }
+
+  .title-column div {
+    padding: 14px 10px 12px 0;
+    font-weight: 700;
+  }
+
+  .row div {
+    flex-grow: 1;
+    text-align: center;
+    margin: 2px;
+    padding: 12px 0 10px 0;
+    background: #e3e3e3;
+    cursor: pointer;
+  }
+
+  .row div.selected {
+    background: rgba(59,155,239,0.7);
+    color: #ffffff;
+  }
+
+  #command {
+    margin: 2px;
+    padding: 12px 10px 10px 10px;
+  }
+
+  #command pre {
+    padding: 0;
+    margin: 0;
+    white-space: pre-wrap;
+  }
+
+</style>
+
+<div class="quick-start">
+  <div class="title-column">
+    <div>PyTorch</div>
+    <div>Your OS</div>
+    <div>CUDA</div>
+    <div>Run:</div>
+  </div>
+  <div class="content-column">
+    <div class="row" id="torch"></div>
+    <div class="row" id="os"></div>
+    <div class="row" id="cuda"></div>
+    <div class="row" id="command"><pre></pre></div>
+  </div>
+</div>
+
+<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
+<script>
+  var torchList = [
+    ['torch-2.2.0', 'PyTorch 2.2.*'],
+    ['no_torch', 'w/o PyTorch'],
+  ];
+
+  var osList = [
+    ['linux', 'Linux'],
+    ['macos', 'Mac'],
+  ];
+
+  var cudaList = [
+    ['cu118', '11.8'],
+    ['cu121', '12.1'],
+    ['cpu', 'CPU'],
+  ];
+
+  torchList.forEach(x => $("#torch").append(`<div id="${x[0]}">${x[1]}</div>`));
+  osList.forEach(x => $("#os").append(`<div id="${x[0]}">${x[1]}</div>`));
+  cudaList.forEach(x => $("#cuda").append(`<div id="${x[0]}">${x[1]}</div>`));
+
+  function updateCommand() {
+    var torch = $("#command").attr("torch");
+    var os = $("#command").attr("os");
+    var package = $("#command").attr("package");
+    var cuda = $("#command").attr("cuda");
+    
+    if (os == "macos" && cuda != "cpu") {
+      $("#command pre").text('# macOS binaries do not support CUDA');
+    }
+    if (cuda != "cpu" && torch == "no_torch") {
+      $("#command pre").text('# GPU acceleration is not available without PyTorch.');
+    }
+
+    if (os == "linux" && cuda != "cpu" && torch != "no_torch"){
+      $("#command pre").text(`git clone https://github.com/graphnet-team/graphnet.git\ncd graphnet\n\npip install -r requirements/torch_${$("#command").attr("cuda")}.txt -e .[torch, develop]`);
+    }
+    else if (os == "linux" && cuda == "cpu" && torch != "no_torch"){
+      $("#command pre").text(`git clone https://github.com/graphnet-team/graphnet.git\ncd graphnet\n\npip install -r requirements/torch_${$("#command").attr("cuda")}.txt -e .[torch, develop]`);
+    }
+    else if (os == "linux" && cuda == "cpu" && torch == "no_torch"){
+      $("#command pre").text(`# Installations without PyTorch are intended for file conversion only\ngit clone https://github.com/graphnet-team/graphnet.git\ncd graphnet\n\npip install -r requirements/torch_${$("#command").attr("cuda")}.txt -e .[develop]`);
+    }
+
+    if (os == "macos" && cuda == "cpu" && torch != "no_torch"){
+      $("#command pre").text(`git clone https://github.com/graphnet-team/graphnet.git\ncd graphnet\n\npip install -r requirements/torch_macos.txt -e .[torch, develop]`);
+    }
+    if (os == "macos" && cuda == "cpu" && torch == "no_torch"){
+      $("#command pre").text(`# Installations without PyTorch are intended for file conversion only\ngit clone https://github.com/graphnet-team/graphnet.git\ncd graphnet\n\npip install -r requirements/torch_macos.txt -e .[develop]`);
+    }
+  }
+
+  $(".quick-start .content-column .row div").click(function() {
+    $(this).parent().children().removeClass("selected");
+    $(this).addClass("selected");
+    $("#command").attr($(this).parent().attr("id"), $(this).attr("id"));
+    updateCommand();
+  });
+
+  $("#torch").children().get(0).click();
+  $("#linux").click();
+  $("#pip").click();
+  $("#cpu").click();
+
+</script>
diff --git a/docs/source/substitutions.rst b/docs/source/substitutions.rst
new file mode 100644
index 000000000..60dc3602a
--- /dev/null
+++ b/docs/source/substitutions.rst
@@ -0,0 +1,12 @@
+.. |graphnet| image:: ../../../assets/identity/favicon.svg
+   :width: 25px
+   :height: 25px
+   :alt: graphnet
+   :align: bottom
+   
+.. |graphnet-header| image:: ../../../assets/identity/favicon.svg
+   :width: 50px
+   :height: 50px
+   :alt: graphnet
+   :align: bottom
+   
diff --git a/requirements/torch_gpu.txt b/requirements/torch_cu118.txt
similarity index 100%
rename from requirements/torch_gpu.txt
rename to requirements/torch_cu118.txt
diff --git a/requirements/torch_cu121.txt b/requirements/torch_cu121.txt
new file mode 100644
index 000000000..6577d22cc
--- /dev/null
+++ b/requirements/torch_cu121.txt
@@ -0,0 +1,4 @@
+# Contains packages requirements for GPU installation
+--find-links https://download.pytorch.org/whl/torch_stable.html
+torch==2.2.0+cu118
+--find-links https://data.pyg.org/whl/torch-2.2.0+cu121.html