Unconditional Image Generation
Diffusers
Safetensors
English
fit
image-generation
class-conditional
imagenet
Instructions to use BiliSakura/FiT-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/FiT-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/FiT-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

- Xet hash:
- 0a17159481981211e246f79bba4725fa9f305638c2e544cf609620bfddba653d
- Size of remote file:
- 127 kB
- SHA256:
- 5e38af76d6f83632058c958517367d351c4a4c8d6d03eb65e337f38ebc977f68
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