Instructions to use backnotprop/np_cr_model4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use backnotprop/np_cr_model4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("backnotprop/np_cr_model4") prompt = "spiral wave flower,minimalism,white_background,abstract,photoshop generated abstract on a white background" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 79cfff182a5350b278d4e98c9a4e74cc0271e9a09eb6e1f72497c2007c2d5834
- Size of remote file:
- 1 MB
- SHA256:
- 21a9ceb23ae7ce4a493bff4f0dc67b8d29cd664fd6d97aeb041a6e9be1645531
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