Instructions to use buildborderless/FLUX.MF-Lightning-Inpainting-8step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use buildborderless/FLUX.MF-Lightning-Inpainting-8step with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("buildborderless/FLUX.MF-Lightning-Inpainting-8step", 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:
- 1b51abb7de534dafa2d53afb0e6f3939af08e90ddaa2c21b1492b93b9747d33c
- Size of remote file:
- 4.28 GB
- SHA256:
- ca46c5f7b5de02caee7c069f2aedbf628af8def8578319ceae3be1588d448448
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