santibatte / diffusion-models-class

Materials for the Hugging Face Diffusion Models Course

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Hugging Face Diffusion Models Course

In this free course, you will:

  • πŸ‘©β€πŸŽ“ Study the theory behind diffusion models
  • 🧨 Learn how to generate images and audio with the popular πŸ€— Diffusers library
  • πŸ‹οΈβ€β™‚οΈ Train your own diffusion models from scratch
  • πŸ“» Fine-tune existing diffusion models on new datasets
  • πŸ—Ί Explore conditional generation and guidance
  • πŸ§‘β€πŸ”¬ Create your own custom diffusion model pipelines

Register via the signup form and then join us on Discord to get the conversations started.

Syllabus

πŸ“† Publishing date πŸ“˜ Unit πŸ‘©β€πŸ’» Hands-on
TBA 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!

Prerequisites

  • Good skills in Python 🐍
  • Basics in Deep Learning and Pytorch

If it's not the case yet, you can check these free resources:

FAQ

Is this class free?

Yes, totally free πŸ₯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) πŸ€—.

You can create one here πŸ‘‰ https://huggingface.co/join

What’s 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).

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Materials for the Hugging Face Diffusion Models Course

License:Apache License 2.0