models.yaml can serve as a base for expanding our support for other versions of Latent/Stable Diffusion.
Contained are parameters for default width/height, as well as where to find the config and weights for this model.
Adding a new model is as simple as adding to this file.
Fixed merging embeddings based on the changes made in textual inversion. Tested and working. Inverted their logic to prioritize Stable Diffusion implementation over alternatives, but left the option for alternatives to still be used.
* Optimizations to the training model
Based on the changes made in
textual_inversion I carried over the relevant changes that improve model training. These changes reduce the amount of memory used, significantly improve the speed at which training runs, and improves the quality of the results.
It also fixes the problem where the model trainer wouldn't automatically stop when it hit the set number of steps.
* Update main.py
Cleaned up whitespace
