In this free course, you will:
- π©βπ Study the theory behind diffusion models
- 𧨠Learn how to generate images and audio with the popular π€ Diffusers library
- ποΈββοΈ Train your own diffusion models from scratch
- π» Fine-tune existing diffusion models on new datasets
- πΊ Explore conditional generation and guidance
- π§βπ¬ Create your own custom diffusion model pipelines
Register via the signup form and then join us on Discord to get the conversations started.
π Publishing date | π Unit | π©βπ» Hands-on |
---|---|---|
November 28, 2022 | An Introduction to Diffusion Models | Introduction to Diffusers and Diffusion Models From Scratch |
TBA | Fine-Tuning and Guidance | Fine-Tuning a Diffusion Model on New Data and Adding Guidance |
TBA | Stable Diffusion Intro | Exploring a Powerful Text-Conditioned Latent Diffusion Model |
TBA | Stable Diffusion Deep Dive | Fine-Tuning, Sampling Tricks and Custom Pipelines |
More information coming soon!
- Good skills in Python π
- Basics in Deep Learning and Pytorch
If it's not the case yet, you can check these free resources:
- Python: https://www.udacity.com/course/introduction-to-python--ud1110
- Intro to Deep Learning with PyTorch: https://www.udacity.com/course/deep-learning-pytorch--ud188
- PyTorch in 60min: https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
Is this class free?
Yes, totally free π₯³.
Do I need to have a Hugging Face account to follow the course?
Yes, to push your custom models and pipelines to the hub, you need an account (it's free) π€.
You can create one here π https://huggingface.co/join
Whatβs the format of the class?
The course will consist of at least 4 Units. More will be added as time goes on, on topics like diffusion for audio.
Each unit consists of some theory and background alongisde one or more hands-on notebooks. Some units will also contain suggested projects and we'll have competitions and swag for the best pipelines and demos (more details TDB).