Diffusers
Safetensors
OrbitQuantComponentArtifact
orbitquant
quantized
diffusion-transformer
8-bit precision
Instructions to use WaveCut/Z-Image-Turbo-OrbitQuant-W3A3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Z-Image-Turbo-OrbitQuant-W3A3 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-W3A3", 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: 735 Bytes
38a615b 9bf7a15 38a615b 8b569d5 38a615b 8b569d5 9bf7a15 8b569d5 9bf7a15 38a615b | 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 26 27 28 | {
"quant_method": "orbitquant",
"weight_bits": 3,
"activation_bits": 3,
"rotation": "rpbh",
"rotation_seed": 0,
"block_size": "paper",
"codebook": "lloyd_max",
"codebook_version": 2,
"codebook_dtype": "float32",
"row_norm_dtype": "bfloat16",
"activation_norm_dtype": "float32",
"activation_eps": 1e-10,
"weight_pack_dtype": "uint8",
"target_policy": "z_image",
"adaln_policy": "int4_rtn",
"adaln_group_size": 64,
"modules_to_not_convert": [],
"modules_dtype_dict": {},
"artifact_format_version": 1,
"runtime_mode": "auto_fused",
"activation_kernel_backend": "auto",
"packed_matmul_block_m": 64,
"packed_matmul_block_n": 64,
"packed_matmul_block_k": 128,
"packed_matmul_num_warps": 4
}
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