Instructions to use unsloth/Z-Image-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use unsloth/Z-Image-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("unsloth/Z-Image-Turbo", 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
File size: 527 Bytes
dd53895 | 1 2 3 4 5 6 7 8 9 10 | Z-Image-Turbo is licensed under the Apache License, Version 2.0.
Copyright Alibaba Group.
This repository is an unmodified mirror of Tongyi-MAI/Z-Image-Turbo, republished by Unsloth so that a quantised
checkpoint of this model can source its companion components (VAE, text encoder, tokenizer,
scheduler) from a single org. The weights are byte for byte those of the source repository.
Not an official Tongyi product and not endorsed by Tongyi.
See LICENSE for the full terms, which are the upstream terms and are unchanged.
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