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
Download vae/diffusion_pytorch_model.safetensors from tiny-random/z-image: direct link, hf CLI and curl.
- Browser
- Download file 456 kB
-
https://huggingface.co/tiny-random/z-image/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://tiny-random/z-image/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/tiny-random/z-image/resolve/main/vae/diffusion_pytorch_model.safetensors
456 kB
- Xet hash:
- f80c9d462b6b3e4ce3954e69e0357f5a9fea1135c8af4f10f7b838cd47364c31
- Size of remote file:
- 456 kB
- SHA256:
- 2e71547b596ef6dfd8f8d09d61aadc533353269654c9b07b60e33a8c0472161c
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