Added working conditional MNIST generation notebook.

.gitignore

@@ -1,2 +1,3 @@
 /venv
-docs/.DS_Store
+docs/.DS_Store
+diffusion-models/notebooks/mnist_data/

diffusion-models/requirements.txt

@@ -1,4 +1,6 @@
 torch==2.3.0
 torchvision==0.18.0
 matplotlib==3.9.0
-seaborn==0.13.2
+seaborn==0.13.2
+diffusers==0.28.2
+transformers==4.41.2

docs/hf_diffusers/hf_mnist_gen.md

@@ -0,0 +1,49 @@
+In this section we will introduce a core component of the Diffusers library `UNet2DModel`. This page will closely follow the notebook `hf_diffusers_mnist.ipynb`, so if you're interested in a quick run through and want to play around yourself, then check that out. Here, we will go through the code in more detail and explain the different components of the model, but feel free to refer back to this page.
+
+
+
+## `UNet2DModel`
+The `UNet2DModel` is a 2D U-Net model that is used for image generation. It abstracts out all of the annoying details of building the model, and allows you to focus on the important parts of your project.
+
+
+``` python
+model = UNet2DModel(
+    sample_size=28,                  # (1)
+    in_channels=1,                   # (2)
+    out_channels=1,                  # (3)
+    layers_per_block=1,              # (4)
+    block_out_channels=(8, 16, 32),  # (5)
+    down_block_types=(
+        "DownBlock2D",
+        "DownBlock2D",
+        "DownBlock2D",
+    ),
+    up_block_types=(
+        "UpBlock2D",
+        "UpBlock2D",
+        "UpBlock2D",
+    ),
+    num_class_embeds=10,              # (6)
+    norm_num_groups=1,                # (7)
+)
+```
+
+1.  The size of the input image. In this case, it is 28x28 pixels
+2.  The number of channels in the input image. In this case, it is 1, as the images are grayscale, but you would use 3 for RGB images
+3.  The number of channels in the output image. In this case, it is 1, as the images are grayscale, but you would use 3 for RGB images
+4.  The number of layers in each block
+5.  The number of output channels in each block - in a convolutional neural network, the number of channels is the number of filters that are applied to the input image.
+6.  The number of classes your dataset has if you are doing conditional generation.
+7.  The number of groups to use for the normalization layer. This is a hyperparameter that you can tune to improve the performance of your model.
+
+There are a number of additional parameters, but these are the most important ones to understand when you are getting started with the `UNet2DModel`. Let's look at the block types in more detail, and some of the additional paramters
+
+## Further reading
+<div class="grid cards" markdown>
+
+-   :fontawesome-solid-book-open:{ .lg .middle } [__CI/CD - Pre-commit resources__](../resources/references.md#pre-commit)
+
+    ---
+    Information on GitHub Actions, Black, Flake8, Mypy, Isort, and Git Hooks
+
+</div>

docs/hf_diffusers/index.md

@@ -0,0 +1,4 @@
+# Hugging Face Diffusers
+In this section, we make life easy for ourselves and use the Hugging Face Diffusers Library. We will look at two main tasks: image generation and ECG generation. We will start with image generation, and in doing so, we'll walk through most of the building blocks required to understand the second task.
+
+Let's get started!

docs/index.md

@@ -2,9 +2,9 @@
     <img src="./imgs/full_acc.png" alt="Logo" width=500>
   </a>
 
-# COURSE TITLE
+# Introduction to diffusion models in generative AI
 
-Welcome to the material for COURSE NAME.
+Welcome to the material for Introduction to diffusion models in generative AI.
 
 Please check the [official Mkdocs Material documentation](https://squidfunk.github.io/mkdocs-material/) for more information on how to use this template.
 

mkdocs.yml

@@ -1,6 +1,6 @@
-site_name: SITE NAME
-repo_url: https://github.com/acceleratescience/REPO-TITLE
-site_url: https://acceleratescience.github.io/REPO-TITLE/
+site_name: Introduction to diffusion models in generative AI
+repo_url: https://github.com/acceleratescience/diffusion-models
+site_url: https://acceleratescience.github.io/diffusion-models/
 nav:
   - Home: 
     - Welcome!: index.md
@@ -10,10 +10,10 @@ nav:
   - Multi Page 1:
     - Subpage 1: multi_1/subpage_1.md
     - Subpage 2: multi_1/subpage_2.md
-  - Multi Page 2:
-    - multi_2/index.md
-    - Page 1: multi_2/subpage_1.md
-    - Page 2: multi_2/subpage_2.md
+  - Hugging Face Diffusers:
+    - hf_diffusers/index.md
+    - Image Generation: hf_diffusers/hf_mnist_gen.md
+    - ECG Generation: hf_diffusers/hf_ecg_gen.md
   - Resources:
     - resources/index.md
     - Slides: resources/slides.md