Instructions to use fal/Z-Image-Turbo-Control-2.1-Int8Dynamic-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-2.1-Int8Dynamic-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-2.1-Int8Dynamic-FlashPack", 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
- Xet hash:
- c7db2d457a5eb553667c0b380d8362b9914174bf0b17c359a345b3bb7af8e557
- Size of remote file:
- 16 GB
- SHA256:
- 05e455ea5e440919b6ba2001fdd6023d85e3dcb5a6799b92c7334efda8750237
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