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", 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:
- fc30656ddd9c485eee84bc6c055f71296f9c6f0e2ae260ed22d5a89d869d1dd0
- Size of remote file:
- 1.11 MB
- SHA256:
- c5c82470405f51dc4a60a90cae17a22681bda4ecdc3bd80e86f72da843c1d125
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