Instructions to use tuanio/ddpm-cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tuanio/ddpm-cifar10 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tuanio/ddpm-cifar10", 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
- Xet hash:
- 549dd09a806b14b05f0628aa9389387e175a4908baef39c8035331d4874f5afb
- Size of remote file:
- 10.2 MB
- SHA256:
- 6b183bfb567ac9325bf8968683f69f8c7ebcc905304b639bced378dfdc794d09
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