huggingface/diffusion-models-class

Hugging Face Diffusion Models Course

     

In this free course, you will:

• 👩‍🎓 Study the theory behind diffusion models
• 🧨 Learn how to generate images and audio with the popular 🤗 Diffusers library
• 🏋️‍♂️ Train your own diffusion models from scratch
• 📻 Fine-tune existing diffusion models on new datasets
• 🗺 Explore conditional generation and guidance
• 🧑‍🔬 Create your own custom diffusion model pipelines

Register via the signup form and then join us on Discord to get the conversations started. Instructions on how to join specific categories/channels are here.

Syllabus

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:

• 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 60 min: https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html

FAQ

Is this class free?

Yes, totally free 🥳.

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) 🤗.

You can create one here 👉 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 alongside 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).

🌎 Languages and translations

Members of the 🤗 community have begun translating the course! We're planning to host this course on the Hugging Face website, so if you're interested in contributing a translation, we recommend waiting until we've formatted the English content in it's final form.