Instructions to use Disty0/Z-Image-Turbo-SDNQ-uint4-svd-r32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Disty0/Z-Image-Turbo-SDNQ-uint4-svd-r32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Disty0/Z-Image-Turbo-SDNQ-uint4-svd-r32", torch_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:
- fedaad6e1b926ed836a5c292032d26298e5ee8fe365f92f7492ee5e8e7866d85
- Size of remote file:
- 3.48 GB
- SHA256:
- 3e26ae546012bb5ca0fc7459f9ae788dcd9921fe1cda28adfb43472dd03bd3cf
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