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HomeLLMsZ Image Turbo SDNQ uint4 svd r32

Z Image Turbo SDNQ uint4 svd r32

by Disty0

Open source · 11k downloads · 54 likes

2.2
(54 reviews)ImageAPI & Local
About

This model, "Z Image Turbo SDNQ uint4 svd r32," is an optimized and quantized version of the Z-Image-Turbo model, utilizing 4-bit quantization (UINT4) with a rank-32 singular value decomposition (SVD). It delivers performance comparable to the original BF16 version while significantly reducing size and memory requirements, making it more accessible for deployment on resource-constrained devices. Its core capabilities include generating and editing images from text prompts while maintaining visual quality despite compression. Ideal for applications requiring a balance between performance and efficiency—such as mobile creative tools or embedded solutions—it stands out for its lightweight design and fast execution speed.

Documentation

4 bit (UINT4 with SVD rank 32) quantization of Tongyi-MAI/Z-Image-Turbo using SDNQ.

Usage:

Code
pip install sdnq
Py
import torch
import diffusers
from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers
from sdnq.common import use_torch_compile as triton_is_available
from sdnq.loader import apply_sdnq_options_to_model

pipe = diffusers.ZImagePipeline.from_pretrained("Disty0/Z-Image-Turbo-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)

# Enable INT8 MatMul for AMD, Intel ARC and Nvidia GPUs:
if triton_is_available and (torch.cuda.is_available() or torch.xpu.is_available()):
    pipe.transformer = apply_sdnq_options_to_model(pipe.transformer, use_quantized_matmul=True)
    pipe.text_encoder = apply_sdnq_options_to_model(pipe.text_encoder, use_quantized_matmul=True)
    pipe.transformer = torch.compile(pipe.transformer) # optional for faster speeds

pipe.enable_model_cpu_offload()

prompt = "Young Chinese woman in red Hanfu, intricate embroidery. Impeccable makeup, red floral forehead pattern. Elaborate high bun, golden phoenix headdress, red flowers, beads. Holds round folding fan with lady, trees, bird. Neon lightning-bolt lamp (⚡️), bright yellow glow, above extended left palm. Soft-lit outdoor night background, silhouetted tiered pagoda (西安大雁塔), blurred colorful distant lights."
image = pipe(
    prompt=prompt,
    height=1024,
    width=1024,
    num_inference_steps=9,
    guidance_scale=0.0,
    generator=torch.manual_seed(42),
).images[0]
image.save("z-image-turbo-sdnq-uint4-svd-r32.png")

Original BF16 vs SDNQ quantization comparison:

QuantizationModel SizeVisualization
Original BF1612.3 GBOriginal BF16
SDNQ UINT43.5 GBSDNQ UINT4
Capabilities & Tags
diffuserssafetensorssdnqz_image4-bit
Links & Resources
Specifications
CategoryImage
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Rating
2.2

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