Instructions to use fal/Z-Image-Turbo-Control-2.0-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-2.0-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-2.0-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:
- b7cabaa99af7660487413b81e04b761c219ba40762da55d5558269830a967f0a
- Size of remote file:
- 18.2 GB
- SHA256:
- aec40cb03c9adfc06ef47c0feff826bc8ef61fed8b4fcbe33e2a357773e8a42d
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