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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3c57169d9c403360b39539b39963509425464850ee5ba58507cc816b36c61660
- Size of remote file:
- 1.41 MB
- SHA256:
- 4edbc5f3277b151aca0d61adfc6f4a8abc583a3835eaa2469a3ee2cc8ba75500
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