🤗 Stable Diffusion Example Usage, How to Test & Deep Dive 😎 (Open AI)
In this video Chris walks through several examples including generating images with Stable Diffusion on the Hugging Face website, the DreamStudio.ai beta site, via a Google Colab instance of Stable Diffusion cloned into that environment and much much more. In addition, Chris reviews the code, makes changes, and shows how to upload an image to upscale or leverage stable diffusion to create better and better images.
Helpful Links:
https://beta.dreamstudio.ai/dream
https://beta.dreamstudio.ai/prompt-guide
https://huggingface.co/spaces/stabili...
AssemblyAI Reference:
https://www.assemblyai.com/blog/how-t...
Colab Link for uploading images: https://colab.research.google.com/dri...
Inside the episode / skip ahead:
0:00 Intro
0:32 Hugging Face Interface for Stable Diffusion
1:01 Stability AI - Dream Studio Login and Settings
1:45 Dream Studio Membership and Credit Usage
2:30 Dream Studio Examples (Darth Vader Unicorn!)
3:50 Prompts and Example Input Queries for Best Results
4:20 Dream Studio Menu Review
4:50 Google Colab with Uploads - Overview
5:50 Run Google Colab of Stable Diffusion - Run in Cloud
7:12 Generating images with my own instance of Stable Diffusion!
8:50 Reviewing images generated from my own instance of Stable Diffusion
9:19 Upsampling / Upload images of my own into Stable Diffusion
10:08 Reviewing Stable Diffusion images generated from original image
10:34 Stable Diffusion source code review - high level
12:12 High level explanation of Stable Diffusion architecture
12:30 Latent text to image diffusion model explanation
12:45 Discussing noise / de-noise process high-level
13:30 The crux of Stable Diffusion - simple explanation
14:25 512 x 512 images and image biasing
15:00 Resource utilization optimization and notes
15:25 Use your own image data for training
16:45 Notes about running in a local environment / low resource environments
17:20 Access and License Acknowledgement Requirements
17:42 Model Details - Developer, Model Type, Language, License, etc.
18:08 Detailed License and Terms Review
19:36 Use Restrictions (Cannot Use For Certain Cases)
21:08 Imagen Abstract and Detailed Research (concepts that support Stable Diffusion)
23:43 Supporting Latent Diffusion Models Research Paper Review
24:52 Example Detailed Image Generation Comparison with Latent Diffusion Models
25:44 Stable Diffusion / Latent Diffusion Core Neural Network Design / Architecture
26:38 Example Installation Steps (very simple to set up a local environment!)
26:55 Example options to set in order to run Stable Diffusion on a laptop or similar environment
27:32 Uses and Direct Use Scenarios
28:00 Misuse, Malicious Use, and Out-of-Scope Use Scenarios
29:30 Limitations and Bias
31:45 Training Data and Subsets used for training - training steps
32:30 Brief discussion on downsampling
33:35 Brief discussion on cross-attention / attention within AI
35:10 Stable Diffusion Checkpoints and Discussion around v1-4
35:45 Hardware used to generate trained Stable Diffusion versions
36:20 FID vs CLIP scores
37:11 Outro
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