Text-to-Image
Diffusers
Safetensors
English
image-generation
class-conditional
imagenet
pixeldit
flow-matching
pixel-space
dit
Instructions to use BiliSakura/PixelDiT-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/PixelDiT-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("BiliSakura/PixelDiT-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "A golden retriever playing in a sunny garden" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- b8faa3bc3643dc13c5e4ad543f160c0127b406e8aee124e3e872fcaecea8acd3
- Size of remote file:
- 17.5 MB
- SHA256:
- 3f289bc05132635a8bc7aca7aa21255efd5e18f3710f43e3cdb96bcd41be4922
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