Diffusers
Safetensors
OrbitQuantComponentArtifact
orbitquant
quantized
diffusion-transformer
8-bit precision
Instructions to use WaveCut/Z-Image-Turbo-OrbitQuant-W2A4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Z-Image-Turbo-OrbitQuant-W2A4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Z-Image-Turbo-OrbitQuant-W2A4", 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
Require OrbitQuant 0.9.0 for mixed-bit artifacts
Browse files
README.md
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Install OrbitQuant and the Hugging Face runtime dependencies:
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```bash
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pip install "orbitquant[hf,kernels]>=0.
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```
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Download this model repository as an OrbitQuant artifact, then load the source Diffusers pipeline with the quantized component patched in:
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Install OrbitQuant and the Hugging Face runtime dependencies:
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```bash
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pip install "orbitquant[hf,kernels]>=0.9.0"
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```
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Download this model repository as an OrbitQuant artifact, then load the source Diffusers pipeline with the quantized component patched in:
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