Instructions to use INCModel/Z-Image-tiny-for-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use INCModel/Z-Image-tiny-for-testing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("INCModel/Z-Image-tiny-for-testing", 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
- Draw Things
- DiffusionBee
File size: 534 Bytes
1f0cd5c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"_class_name": "ZImagePipeline",
"_diffusers_version": "0.38.0.dev0",
"_name_or_path": "/root/.cache/huggingface/hub/models--Tongyi-MAI--Z-Image/snapshots/04cc4abb7c5069926f75c9bfde9ef43d49423021",
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"Qwen3Model"
],
"tokenizer": [
"transformers",
"Qwen2Tokenizer"
],
"transformer": [
"diffusers",
"ZImageTransformer2DModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
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