🔧Installing Dreambooth requires removing certain elements from the command line and API info for paint Hua.
📚Dreambooth provides an extensions tab with options to load different models, including the popular Dream Booth.
⏱️The installation process for Dreambooth may take some time, depending on your GPU.
🔄After installation, restart Dreambooth to load and train your models for image generation.
💡Use specific prompts and negative prompts to train the model and get desired results.
How long does it take to install Dreambooth?
—The installation process may take some time, depending on the GPU you have. On average, it takes around 30 minutes.
Can I train the model to generate images of any subject or object?
—Yes, you can train the model to generate images of any subject or object by providing specific prompts and negative prompts.
What are the recommended settings for training with Dreambooth?
—The recommended settings include setting the max training steps to 1100, learning rate to 0.00001, and using 8-bit Adam with mixed precision.
Can I use my own images for training?
—Yes, you can use your own images for training by specifying the source folder for input images.
What are the best prompts to get accurate and painterly results?
—Using prompts like 'style of Greg rokovsky' and 'award-winning photography' can help achieve more accurate and painterly results.
00:00Learn how to install Dreambooth and set up your first styling fusion model.
01:16Remove unnecessary elements from the command line and API info for paint Hua during installation.
01:58Load the Dream Booth model and install it through the extensions tab.
02:45Restart Dreambooth to complete the installation and open the Dream Booth tab.
04:01Choose a name for your model and select the source checkpoint for training.
04:34Set the required parameters for training, including learning rate and use of 8-bit Adam with mixed precision.
05:02Specify the source folder for input images and provide prompts and negative prompts for training.
06:39Select the desired number of class images and start the training process.
