Instructions to use fal/Z-Image-Turbo-Control-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/Z-Image-Turbo-Control-FlashPack with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/Z-Image-Turbo-Control-FlashPack", 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:
- 443da94359725fbd3116dd847f86154cb44045a4caf3c28eaa65b8286374cb78
- Size of remote file:
- 8.82 GB
- SHA256:
- ae185272a39f55ed2b3a39a00cbb47a49c00fb72935518ae28b65f7a74145cb9
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