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
File size: 856 Bytes
10faabb 71c8f21 10faabb f4b6417 71c8f21 f4b6417 1626224 1251424 39ef596 10faabb | 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 | {
"_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": 2,
"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": "component"
}
|