Instructions to use TheCodingBug/Z-Image-Turbo-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheCodingBug/Z-Image-Turbo-int8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TheCodingBug/Z-Image-Turbo-int8", 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 text_encoder/bugquant_metadata.json from TheCodingBug/Z-Image-Turbo-int8: direct link, hf CLI and curl.
- Browser
- Download file 185 Bytes
-
https://huggingface.co/TheCodingBug/Z-Image-Turbo-int8/resolve/main/text_encoder/bugquant_metadata.json
- Command line
-
hf download hf://TheCodingBug/Z-Image-Turbo-int8/text_encoder/bugquant_metadata.json
-
curl -L -o bugquant_metadata.json https://huggingface.co/TheCodingBug/Z-Image-Turbo-int8/resolve/main/text_encoder/bugquant_metadata.json
185 Bytes
| { | |
| "source_model": "Tongyi-MAI/Z-Image-Turbo", | |
| "subfolder": "text_encoder", | |
| "architecture": "Qwen3ForCausalLM", | |
| "quantization": "int8", | |
| "quantizer": "SDNQ", | |
| "group_size": 0 | |
| } |