diff --git a/.github/workflows/build_docs.yml b/.github/workflows/build_docs.yml
index 800d92bf..e52e71c3 100644
--- a/.github/workflows/build_docs.yml
+++ b/.github/workflows/build_docs.yml
@@ -13,9 +13,6 @@ on:
   # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
 
-permissions: 
-  contents: write
-
 # Workflow run - one or more jobs that can run sequentially or in parallel
 jobs:
   # This workflow contains a single job called "build-docs"
diff --git a/FTorch.md b/FTorch.md
index 12ac20c1..66cad5ab 100644
--- a/FTorch.md
+++ b/FTorch.md
@@ -5,6 +5,7 @@ author: ICCS Cambridge
 license: mit
 github: https://github.com/Cambridge-ICCS
 project_github: https://github.com/Cambridge-ICCS/FTorch
+page_dir: pages
 src_dir: ./src
          ./utils
 output_dir: ./doc
diff --git a/pages/cmake.md b/pages/cmake.md
new file mode 100644
index 00000000..60dd71f8
--- /dev/null
+++ b/pages/cmake.md
@@ -0,0 +1,61 @@
+title: CMake Build Process
+
+Installation of FTorch is done by CMake.
+
+This is controlled by the `CMakeLists.txt` file in `src/`.
+
+## Basic instructions
+
+To build the library, first clone it from github to your local machine and then run:
+```bash
+cd FTorch/src/
+mkdir build
+cd build
+```
+
+Then invoke CMake with the Release build option, plus any other options as required
+from the table below in [CMake build options](#cmake-build-options)
+(note: you will likely _need_ to add some of these options to ):
+```bash
+cmake .. -DCMAKE_BUILD_TYPE=Release
+```
+
+Finally build and install the library:
+```bash
+cmake --build . --target install
+```
+
+## CMake build options
+
+It is likely that you will need to provide at least the `CMAKE_PREFIX_PATH` flag.  
+The following CMake flags are available and can be passed as arguments through `-D<Option>=<Value>`:
+
+| Option                                                                                            | Value                        | Description                                                   |
+| ------------------------------------------------------------------------------------------------- | ---------------------------- | --------------------------------------------------------------|
+| [`CMAKE_Fortran_COMPILER`](https://cmake.org/cmake/help/latest/variable/CMAKE_LANG_COMPILER.html) | `ifort` / `gfortran`         | Specify a Fortran compiler to build the library with. This should match the Fortran compiler you're using to build the code you are calling this library from.        |
+| [`CMAKE_C_COMPILER`](https://cmake.org/cmake/help/latest/variable/CMAKE_LANG_COMPILER.html)       | `icc` / `gcc`                | Specify a C compiler to build the library with                |
+| [`CMAKE_CXX_COMPILER`](https://cmake.org/cmake/help/latest/variable/CMAKE_LANG_COMPILER.html)     | `icpc` / `g++`               | Specify a C++ compiler to build the library with              |
+| [`CMAKE_PREFIX_PATH`](https://cmake.org/cmake/help/latest/variable/CMAKE_PREFIX_PATH.html)        | `</path/to/libTorch/>`       | Location of Torch installation<sup>1</sup>                    |
+| [`CMAKE_INSTALL_PREFIX`](https://cmake.org/cmake/help/latest/variable/CMAKE_INSTALL_PREFIX.html)  | `</path/to/install/lib/at/>` | Location at which the library files should be installed. By default this is `/usr/local` |
+| [`CMAKE_BUILD_TYPE`](https://cmake.org/cmake/help/latest/variable/CMAKE_BUILD_TYPE.html)          | `Release` / `Debug`          | Specifies build type. The default is `Debug`, use `Release` for production code|
+| `ENABLE_CUDA`                                                                                     | `TRUE` / `FALSE`             | Specifies whether to check for and enable CUDA<sup>2</sup> |
+
+
+<sup>1</sup> _The path to the Torch installation needs to allow cmake to locate the relevant Torch cmake files.  
+      If Torch has been [installed as libtorch](https://pytorch.org/cppdocs/installing.html)
+      then this should be the absolute path to the unzipped libtorch distribution.
+      If Torch has been installed as PyTorch in a python [venv (virtual environment)](https://docs.python.org/3/library/venv.html),
+      e.g. with `pip install torch`, then this should be `</path/to/venv/>lib/python<3.xx>/site-packages/torch/`._
+
+<sup>2</sup> _This is often overridden by PyTorch. When installing with pip, the `index-url` flag can be used to ensure a CPU or GPU only version is installed, e.g.
+      `pip install torch --index-url https://download.pytorch.org/whl/cpu`
+      or
+      `pip install torch --index-url https://download.pytorch.org/whl/cu118`
+      (for CUDA 11.8). URLs for alternative versions can be found [here](https://pytorch.org/get-started/locally/)._
+
+For example, to build on a unix system using the gnu compilers and install to `$HOME/FTorchbin/`
+we would need to run:
+```
+
+```
+
diff --git a/pages/index.md b/pages/index.md
new file mode 100644
index 00000000..98f8d189
--- /dev/null
+++ b/pages/index.md
@@ -0,0 +1,30 @@
+title: Other documentation
+
+[TOC]
+
+## GPU Support
+
+In order to run a model on GPU, two main changes are required:
+
+1) When saving your TorchScript model, ensure that it is on the GPU.
+For example, when using [pt2ts.py](utils/pt2ts.py), this can be done by
+uncommenting the following lines:  
+
+``` { .python}
+device = torch.device('cuda')
+trained_model = trained_model.to(device)
+trained_model.eval()
+trained_model_dummy_input_1 = trained_model_dummy_input_1.to(device)
+trained_model_dummy_input_2 = trained_model_dummy_input_2.to(device)
+```
+Note: this also moves the dummy input tensors to the GPU. This is not necessary for
+saving the model, but the tensors must also be on the GPU to test that the models runs.
+
+2) When calling `torch_tensor_from_blob` in Fortran, the device for the input tensor(s),
+   but not the output tensor(s), should be set to `torch_kCUDA`, rather than
+   `torch_kCPU`. This ensures that the inputs are on the same device as the model.
+
+## Useful resources
+
+* [The libtorch API](https://pytorch.org/cppdocs/api/library_root.html)
+
diff --git a/pages/transposing.md b/pages/transposing.md
new file mode 100644
index 00000000..4443ba6f
--- /dev/null
+++ b/pages/transposing.md
@@ -0,0 +1,15 @@
+title: When to transpose data
+
+In the ResNet18 example, it was expected that the shape and indices of `in_data` in resnet_infer_fortran.f90 match that of `input_batch` in resnet18.py, i.e. `in_data(i, j, k, l) ==  input_batch[i, j, k, l]`.
+
+Since C is row-major (rows are contiguous in memory), whereas Fortran is column-major (columns are contiguous), it is therefore necessary to perform a transpose when converting from the NumPy array to the Fortran array to ensure that their indices are consistent.
+
+In this example code, the NumPy array is transposed before being flattened and saved to binary, allowing Fortran to `reshape` the flatted array into the correct order.
+
+An alternative would be to save the NumPy array with its original shape, but perform a transpose during or after reading the data into Fortran, e.g. using:
+
+```
+in_data = reshape(flat_data, shape(in_data), order=(4,3,2,1))
+```
+
+For more general use, it should be noted that the function used to create the input tensor from `input_batch`, `torch_tensor_from_blob`, performs a further transpose, which is required to allow the tensor to interact correctly with the model.
diff --git a/pages/troubleshooting.md b/pages/troubleshooting.md
new file mode 100644
index 00000000..999e02bf
--- /dev/null
+++ b/pages/troubleshooting.md
@@ -0,0 +1,30 @@
+title: Troubleshooting
+
+If you are experiencing problems building or using FTorch please see below for guidance on common problems.
+
+[TOC]
+
+## Windows
+
+If possible we recommend using the [Windows Subsystem for Linux](https://learn.microsoft.com/en-us/windows/wsl/) (WSL) to build the library.
+In this case the build process is the same as for a Linux environment.
+
+If you need 
+
+### Visual Studio
+
+Use Visual Studio and the Intel Fortran Compiler  
+In this case you must install 
+* [Visual Studio](https://visualstudio.microsoft.com/)
+* [Intel OneAPI Base and HPC toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html) (ensure that the Intel Fortran compiler and VS integration is selected).
+
+You should then be able to build from CMD following the 
+
+### MinGW
+
+It may be tempting to build on Windows using MinGW.
+However, [libtorch does not currently support MinGW](https://github.com/pytorch/pytorch/issues/15099).
+Instead please build using Visual Studio and the intel fortran compiler (ifort) as
+detailed in the project README.
+
+