Skip to content

Latest commit

 

History

History
45 lines (32 loc) · 3.73 KB

File metadata and controls

45 lines (32 loc) · 3.73 KB

Diffusion Model Course by Huggingface

License   GitHub forks   GitHub watchers  

Made with Jupyter   PyTorch

Hugging Face Logo (Click the image to see some magic! 👀)

About Huggingface and this course:

Huggingface is an AI community on a mission to democratize machine learning models. They open-source AI by providing a one-stop-shop of resources, ranging from models (+30k), datasets (+5k), ML demos (+2k) and libraries. You can deploy your model to open-source it on huggingface, or you can release Dataset you have prepared.

This course aims to teach the impact of Generative Adversarial Network(GAN) and understand how they work on very basic level.This course was launched by Huggingface and Lewis Tunstall . The course is absolutely free. 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).

Community:

Discord   Join Discord Server For Huggingface to discuss on the course. Click on the icon to get invite link

Register via the Sign up Form to get started through the class. To discuss about the class, join the discord.

Prerequisites:

  • Good skills in Python
  • Basic in Deep Learning and PyTorch
  • Huggingface 🤗 account to deploy pipelines and models

What will you learn:

  • 👩‍🎓 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

Syllabus:

📆 Publishing Date 📘 Unit 👩‍💻 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