Instructions to use briannlongzhao/basquiat_custom_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use briannlongzhao/basquiat_custom_diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("briannlongzhao/basquiat_custom_diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "a painting of <new1>" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1b82cccb84a7ad61d6a6e6145c4d4240b9be3eced7dd2f638ff316b771b40cb4
- Size of remote file:
- 102 MB
- SHA256:
- 66093d21b44a43efd64bd2c048ad5f16e72b40a21b56e6f717c0b8b015186114
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