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:
- 024f7a968081410655d413ff64947362e7f37128c6ae5ad5add7de8b68a788ba
- Size of remote file:
- 110 kB
- SHA256:
- dfed0852cbe4af2a2121dbb20fa48a8bfb9900f346c68fa6bc8b92c07c8e1ee8
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