Instructions to use tiny-random/z-image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tiny-random/z-image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tiny-random/z-image", 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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- f80c9d462b6b3e4ce3954e69e0357f5a9fea1135c8af4f10f7b838cd47364c31
- Size of remote file:
- 456 kB
- SHA256:
- 2e71547b596ef6dfd8f8d09d61aadc533353269654c9b07b60e33a8c0472161c
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