Diffusers
Safetensors
OrbitQuantComponentArtifact
orbitquant
quantized
diffusion-transformer
8-bit precision
Instructions to use WaveCut/Z-Image-Turbo-OrbitQuant-W4A4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Z-Image-Turbo-OrbitQuant-W4A4 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-W4A4", 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
| { | |
| "_class_name": "OrbitQuantComponentArtifact", | |
| "artifact_format": "orbitquant-v1", | |
| "quant_method": "orbitquant", | |
| "source_model_id": "Tongyi-MAI/Z-Image-Turbo", | |
| "source_revision": "f332072aa78be7aecdf3ee76d5c247082da564a6", | |
| "source_license": "apache-2.0", | |
| "component": "transformer", | |
| "weight_name": "model.safetensors", | |
| "quantization_config": "quantization_config.json", | |
| "manifest": "orbitquant_manifest.json", | |
| "codebooks": "orbitquant_codebooks.safetensors", | |
| "rotations": "orbitquant_rotations.safetensors", | |
| "weight_bits": 4, | |
| "activation_bits": 4, | |
| "codebook_version": 2, | |
| "target_policy": "z_image", | |
| "runtime_mode": "auto_fused", | |
| "activation_kernel_backend": "auto", | |
| "activation_eps": 1e-10, | |
| "quantization_device": "cuda", | |
| "weight_quantization_backend": "triton_cuda", | |
| "quantization_staging_mode": "streaming" | |
| } | |