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
File size: 1,818 Bytes
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"vae_model_name_or_path": "nyu-visionx/RAE-dinov2-wReg-base-ViTXL-n08"
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} |