Text-to-Image
Diffusers
Safetensors
English
fd-loss
jit
imf
pmf
image-generation
class-conditional
imagenet
Instructions to use BiliSakura/FD-Loss-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/FD-Loss-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/FD-Loss-diffusers", torch_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
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- cd191ab114132228eca326d84d5bee00d6c53b7b75eea920f860f5bd6322b7d4
- Size of remote file:
- 155 kB
- SHA256:
- 03188030ad81ad8a3d5b9ace40731a4c3f8bd540e355e465cf80fe2f13bdc17a
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