Unconditional Image Generation
Diffusers
Safetensors
RAEDiTPipeline
rae
rae-dit
diffusion-transformer
imagenet-256
arxiv:2510.11690
Instructions to use plugyawn/rae-dit-s-ep14-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use plugyawn/rae-dit-s-ep14-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("plugyawn/rae-dit-s-ep14-diffusers", 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
Download vae/config.json from plugyawn/rae-dit-s-ep14-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 5.69 MB
-
https://huggingface.co/plugyawn/rae-dit-s-ep14-diffusers/resolve/main/vae/config.json
- Command line
-
hf download hf://plugyawn/rae-dit-s-ep14-diffusers/vae/config.json
-
curl -L -o config.json https://huggingface.co/plugyawn/rae-dit-s-ep14-diffusers/resolve/main/vae/config.json
5.69 MB
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