Mastering Diffusion Models: Prompting & Fine-Tuning Techniques

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Learn how to effectively prompt vision models using text inputs, coordinates, and bounding boxes. Discover how to tune hyper-parameters like guidance scale, strength, and the number of inference steps to achieve the desired results. 

Key Takeaways:

  • In-painting for Image Modification: Gain practical experience replacing parts of an image with generated content through in-painting. This technique integrates object detection, image segmentation, and image generation to update images seamlessly.
  • Fine-tuning Diffusion Models: Master the art of fine-tuning diffusion models for precise control over image generation. This will enable you to create concrete, personalized images beyond generic outputs.

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