Instructions to use blanchon/dc_flux_krea_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use blanchon/dc_flux_krea_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("blanchon/dc_flux_krea_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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2ec3c5ec83109b41e98e8fbee4862875c8d9ed42b43ea5f4928879a65ce448fd
- Size of remote file:
- 1.35 GB
- SHA256:
- 8b17af9ffd0fe68252baa6ace016fabe2c2bafa6534ba7d72fe7fa78a58423cf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.