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- Dreambooth Motivation
- Fine-Tuning Stable Diffusion with Your Photos
- In Practice: Generating Cool Images
- Final Thoughts
Feel free to skip this section if you’re not particularly interested in the theory behind the approach and prefer to dive straight into the implementation. The first step towards creating images of ourselves using DreamBooth is to teach the model how we look. To do so, we’ll follow a special procedure to implant ourselvesinto the output space of an...
Three important elements are needed before fine-tuning our model: hardware, photos, and the pre-trained stable diffusion model. The original implementation requires a large amount of GPU resources to train, making it difficult for common Machine Learning practitioners to reproduce. However, a community in discord has developed an unofficial impleme...
Creating great images requires both practice and patience. However, this process can be alleviated by using the right tools. The one we’re about to show you is truly mind-blowing; it’s so versatile that we can’t recommend it enough! It’s a WebUIthat makes the entire process more interactive and fun. To use it, we must run a web server and follow th...
Stable Diffusion signified one of the biggest leaps toward democratizing large image synthesis models. Techniques such as DreamBooth (and their community-driven implementations) allow us to reap the benefits of these models even further, with imagination being our only limit. We are extremely excited to know where this new democratic AI paradigm wi...
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