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
Refresh OrbitQuant runtime usage examples
Browse files- README.md +1 -0
- SHA256SUMS +1 -1
README.md
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torch_dtype=torch.bfloat16,
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device="cuda",
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image = pipe(
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artifact_dir,
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torch_dtype=torch.bfloat16,
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device="cuda",
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runtime_mode="auto_fused",
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image = pipe(
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3d17f4a76f5625cc76d914b5fac8325e79909c82e6420317040b789d8ce0bcaf assets/image_generation_comparison_matrix.webp
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a76152c262ad1463f103956d61deff27192410baeacfdeafe3616dda9c1e0691 benchmark/summary.json
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aea099a0445d60c272a2c45a8c4e88fd4b3cedf7181a4b3600873104eb7a7941 model.safetensors
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b26ab179ce89c72f06c11b4f25ce4631395b54393db27aee969f607d2e40752a README.md
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3d17f4a76f5625cc76d914b5fac8325e79909c82e6420317040b789d8ce0bcaf assets/image_generation_comparison_matrix.webp
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a76152c262ad1463f103956d61deff27192410baeacfdeafe3616dda9c1e0691 benchmark/summary.json
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aea099a0445d60c272a2c45a8c4e88fd4b3cedf7181a4b3600873104eb7a7941 model.safetensors
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