metadata
license: bigscience-openrail-m
Papercute
Papercute is an intentionally overfitted fine-tuning checkpoint for Stable Diffusion 1.x that lets you to create cute papercut images using either txt2img or img2img prompts. The Papercute-100k checkpoint was trained using on 141 curated and captioned images over 100,000 steps.
Training took approximately 11hrs on an Nvidia 3090ti.
Tips for best results
- No keyword is necessary to engage the model. Just load the checkpoint and enter your prompt.
- Works best at around 50 steps
Known Limitations:
- Does not work well with PLMS sampling
- Does not do well with complicated scenes
- Big cats tend to look like doilies. This is due to a particular training image being overempahasized. However the bug/feature has been popular so I've left it in.