If you want to use LEAP on a different Stable Diffusion version, or simply learn how it works, then you find the instructions below very useful.
Authors notes: I'm using Linux (NixOS), while it could work on Windows, I'm not familiar with this operating system. Feel free to reach out for help. Commands are written like this!.
LEAP uses a synthetic dataset, we extract all words from Stable Diffusion and generate "samples" that allow us to associate its images with the weights used to make them.
- Clone this repository and
cdto it. - Install leap_sd:
pip install -e . - run
python training/dataset_creator/sd_extractor.py- For using a custom Stable Diffusion, pass
--pretrained_model_name_or_path, for example:--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5
- For using a custom Stable Diffusion, pass
cdto the training directory of this repo- Check the size of your latent space! (for sd < 2.0 it's 768 and for >= 2.0 it's 1024)
- Run the following training command:
python training/train.py --batch_size=10 --gpus=1 --max_epochs=250 --latent_dim_size=1024
-
Training for SD 1.5
python training/dataset_creator/sd_extractor.py --pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5 python training/train.py --batch_size=10 --gpus=1 --max_epochs=250 --latent_dim_size=768
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