AIAP Sharing Project Topic
Ivan's deadlines:
MILESTONES:
20/3 Assign applications to engineers to do code snippets.\ 21/3 Choose topic\ 23/3 Do code snippets.\ 23/3 Begin writing article.\ 29/3 Submit resources, code samples, code walkthrough for article (for Ivan's review)\ 30/3 Start preparing presentation\ 10/4 Presentation of group sharing.
GOALS:
Write an article (in markdown file) to be published on Medium / Epoch (AISG's forum) on your topic of interest.
Create code samples on GitHub for the code walkthrough in your article.
Present the article to batchmates and engineers.
How does Stable Diffusion work?
How AI Image Generators Work (Stable Diffusion / Dall-E) - Computerphile, 17:49 video
Stable Diffusion in Code (AI Image Generation) - Computerphile, 16:59 video
YouTube - How does Stable Diffusion work? – Latent Diffusion Models EXPLAINED
Encoder Decoder What and Why ? – Simple Explanation
What is Attention Mechanism in Deep Learning ? – Quickly Understand
The Transformer Model\ Machine Learning Mastery, contains math.
Transformer models: an introduction and catalog
Jeremy Howard — The Simple but Profound Insight Behind Diffusion, 1:12:57
At 3:13:\ It's a simple but profound insight. Which is that it's very difficult for a model to generate something creative, and aesthetic, and correct from nothing...or from nothing but a prompt to a question, or whatever. The profound insight is to say, "Well, given that that's hard, why don't we not ask a model to do that directly? Why don't we train a model to do something a little bit better than nothing? And then make a model that — if we run it multiple times — takes a thing that's a little bit better than nothing, and makes that a little bit better still, and a little bit better still." If you run the model multiple times, as long as it's capable of improving the previous output each time, then it's just a case of running it lots of times. And that's the insight behind diffusion models.
GitHub - Stable Diffusion from Scratch (abandoned project)
Title:\ Stable Diffusion with Hugging Face API
1) Intro (JF)
2) What is Stable Diffusion (JH)
3) API Walkthrough (Code should be here)
https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/diffusers_intro.ipynb
a) Model Explanation (JF)
b) Schedulers (JF)
c) forward + backward diffusion -> latent encode , decode (YL)
4) Application -> Text to imageOutput Demo (Shu Ying) 5) End Notes (YL) 6) References 7) Footnotes
References
Stable Diffusion with 🧨 Diffusers
https://huggingface.co/blog/stable_diffusion
The Stable Diffusion Guide 🎨
https://huggingface.co/docs/diffusers/stable_diffusion
Introducing Hugging Face's new library for diffusion models
https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/diffusers_intro.ipynb
example: