Train LORA with 1 Image - Koyha_ss, A1111, Vlad Diffusion

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This article is a summary of a YouTube video "Train a LORA with JUST 1 IMAGE!!! - Koyha_ss, A1111, Vlad Diffusion" by Olivio Sarikas
TLDR Training an AI model like LORA with a diverse range of images and using techniques like chopping the image into smaller sections and adjusting the weight of certain elements in the prompt can lead to impressive and customizable outputs for creating concept art.

Key insights

  • 📣
    Raising awareness and sharing videos can inspire others to share their creative work and ideas, creating a community of people who are willing to explore and experiment with AI.
  • 📐
    Chopping the image into smaller sections and sampling more areas can enhance the training process and improve the overall outcome.
  • 📸
    The speaker used 23 different images with varying scenes and resolutions to train the model, including details and an overview of the subject.
  • 🌳
    Adding keywords to images in training allows for more flexibility in addressing and manipulating specific elements of the image later on.
  • 🎨
    The use of the "ref animated" model in training LORA allows for stable and reliable outputs, making it suitable for creating concept art.
  • 💡
    A workaround to maintain control over the output is to adjust the weight of certain elements in the positive prompt, allowing for a balance between desired and undesired features in the generated output.
  • 📷
    The speaker found that the training process produces hazy images with low contrast, but by editing them in a photo editing software, they were able to achieve amazing results.
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This article is a summary of a YouTube video "Train a LORA with JUST 1 IMAGE!!! - Koyha_ss, A1111, Vlad Diffusion" by Olivio Sarikas
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