Instructions to use Kagerage/craig-wazowski-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kagerage/craig-wazowski-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kagerage/craig-wazowski-style", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Craig-Wazowski-style Dreambooth model trained by Kagerage with TheLastBen's fast-DreamBooth notebook
Test the concept via A1111 Colab fast-Colab-A1111
Or you can run your new concept via diffusers Colab Notebook for Inference
Consistancy is a little rough here, as it seems to struggle choosing between being painterly or realistic, but it works well enough for me. Pre-append every prompt with "GregRutkowski artwork, ", as this seems to give better results than putting it at the end of the prompt. Also use a CFG between 9.0 and 12.0, with a non-ancestral sampler, as these values personally gave me the best quality outputs. Also negative prompts, they help.
NOTE: This model is FP16, so it may have issues working without Xformers, though I haven't tested this myself. Extra note, it was trained on the 768 model, so don't go below that. As with the standard 2.1 768 model, extreme aspect ratios above 768x768 work pretty decently, despite the training images being 1:1.
Sample pictures of this concept:
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