[P] Learn diffusion models with Hugging Face course 🧨

Submitted by lewtun t3_ylz2wh in MachineLearning

Hi there, it's Lewis here from the open-source team at Hugging Face 👋

Since the release of Dalle-Mini and Stable Diffusion a few months ago, you may have seen your timelines filled with impressive text-generated images like the one below:

Image generated with textual inversion and Stable Diffusion

These images are generated by an exciting branch of research called diffusion models, which is rapidly being applied to generate novel structures in computer vision, audio, and even molecular biology 🤯!

To help the community get up to speed on this fast-moving field, we've joined forces with the awesome Jonathan Whitaker to launch a free course on all aspects of diffusion models 🔥

In this 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

The course will be released in a few weeks and you can register via the signup form here: https://huggingface.us17.list-manage.com/subscribe?u=7f57e683fa28b51bfc493d048&id=ef963b4162

Looking forward to meeting you all in the course 🤗!

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Comments

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TheIronMarx t1_iv1ex7x wrote

How technical will this be? What prerequisites would you recommend I understand at minimum?

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leoreno t1_iv2un9v wrote

This is very exciting, looking forward to it!

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wywywywy t1_iv3wpty wrote

So if this turns out to be successful, can we expect more free classes? Or is this a one time thing?

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namfux t1_iv44lmz wrote

Will you show how to do distributed training in the cloud?

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IWantAGrapeInMyMouth t1_iv4fbu1 wrote

Neat! I think one of the biggest considerations to add to this in the future (if not already in it and if this class will be done again) would be to add parts on sparsification/Quantization with models for inference after training. That would really open up the ability to expand usage of the models in things like spaces. Very excited to see what's in the course!

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pdqueiros t1_iv4scgl wrote

Very cool initiative, I've signed up.
Do you have any idea what the course dates would be?

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