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 tokenizer/tokenizer.json from tiny-random/z-image: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/tiny-random/z-image/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://tiny-random/z-image/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/tiny-random/z-image/resolve/main/tokenizer/tokenizer.json
11.4 MB
- Xet hash:
- e20b07fce7dc851dd7ffe618c52a602917db27c9342dbc6d767f710a5c6ea926
- Size of remote file:
- 11.4 MB
- SHA256:
- 05d47c87966b4db779200053de490f89936ed529f8ab889244e271630715fcfe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.