Instructions to use codyreading/custom_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codyreading/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("codyreading/custom_diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "None" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7f5a1213d426142192ea79c471528e2be4f768fa5bdd55fe450dd1f33be370d5
- Size of remote file:
- 176 MB
- SHA256:
- 454262ca49923dbf4a4aedd0fedfd35841c57bb28b14028c3b47ae373671bbda
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.