diff --git a/README.md b/README.md
index 26bb8753..7d670d64 100644
--- a/README.md
+++ b/README.md
@@ -7,8 +7,8 @@ along with metadata about the available models and accelerators, and the output
 is supported on both AMD and Nvidia, with a CPU fallback capable of running on laptop-class machines.
 
 The GUI runs in all major browsers, including on mobile devices, and allows you to select the model and accelerator
-being used, along with the prompt and other image parameters. The last few output images are shown, making it easy to
-refer back to previous parameters.
+being used, along with the prompt and other image parameters. The last few output images are shown below the image
+controls, making it easy to refer back to previous parameters or save an image from earlier.
 
 ![txt2img with example astronaut prompt and image](./docs/readme-preview.png)
 
@@ -22,12 +22,15 @@ Based on guides by:
 ## Features
 
 - REST API server capable of running ONNX models with DirectML acceleration
-  - AMD hardware acceleration
+  - AMD and Nvidia hardware acceleration
   - CPU software fallback
   - multiple schedulers
 - web app to generate and view images
   - can be hosted alongside API or on a CDN
   - built with React and MUI
+- OCI containers
+  - for both API and GUI
+  - for each hardware platform
 - txt2img mode
   - image controls and scheduler selection
   - with recent image history
@@ -53,6 +56,7 @@ Based on guides by:
       - [For CPU on Windows: Install PyTorch CPU](#for-cpu-on-windows-install-pytorch-cpu)
       - [For Nvidia everywhere: Install PyTorch GPU and ONNX GPU](#for-nvidia-everywhere-install-pytorch-gpu-and-onnx-gpu)
     - [Download and convert models](#download-and-convert-models)
+    - [Test the models](#test-the-models)
   - [Usage](#usage)
     - [Configuring and running the server](#configuring-and-running-the-server)
       - [Securing the server](#securing-the-server)
@@ -271,9 +275,6 @@ Run the conversion script with your desired model(s):
 
 This will take a little while to convert each model. Stable diffusion v1.4 is about 6GB, v1.5 is at least 10GB or so.
 
-You should verify that all of the steps up to this point have worked correctly by attempting to run the
-`api/test-setup.py` script, which is a slight variation on the original txt2img script.
-
 If you want to use inpainting, you will need a second model trained for that purpose:
 
 ```shell
@@ -284,6 +285,15 @@ If you want to use inpainting, you will need a second model trained for that pur
 > python convert_stable_diffusion_checkpoint_to_onnx.py --model_path="runwayml/stable-diffusion-inpainting" --output_path=".\models\stable-diffusion-inpainting"
 ```
 
+### Test the models
+
+You should verify that all of the steps up to this point have worked correctly by attempting to run the
+`api/test-setup.py` script, which is a slight variation on the original txt2img script.
+
+If the script works, there will be an image of an astronaut in `outputs/test.png`.
+
+If you get any errors, check [the known errors section](#known-errors-and-solutions).
+
 ## Usage
 
 ### Configuring and running the server