Instructions to use xkronosx/AutoEncoder-mnist-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xkronosx/AutoEncoder-mnist-32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xkronosx/AutoEncoder-mnist-32", 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:
- fdd765656f2e89225534dd530e3aee673c15082acebedc33173d53a4d89b46d7
- Size of remote file:
- 838 kB
- SHA256:
- 424a6ee5f4e45f76a5ae397f31665ab914e0a9953306d32371c01a15b54d3477
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