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ixim
/
Z-Image-INT8

Text-to-Image
Diffusers
Safetensors
English
ZImagePipeline
quanto
int8
z-image
transformer-quantization
Model card Files Files and versions
xet
Community

Instructions to use ixim/Z-Image-INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use ixim/Z-Image-INT8 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("ixim/Z-Image-INT8", 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
  • Local Apps
  • Draw Things
  • DiffusionBee
Z-Image-INT8
14.4 GB
Ctrl+K
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  • 1 contributor
History: 12 commits
ixim's picture
ixim
Update README.md
dc005bc verified 3 months ago
  • scheduler
    Initial commit. 3 months ago
  • test_outputs
    Update README 3 months ago
  • text_encoder
    Initial commit. 3 months ago
  • tokenizer
    Initial commit. 3 months ago
  • transformer
    Initial commit. 3 months ago
  • vae
    Initial commit. 3 months ago
  • zimage_quanto_bench_results
    Update README 3 months ago
  • .gitattributes
    2.94 kB
    Update README 3 months ago
  • README.md
    7.27 kB
    Update README.md 3 months ago
  • model_index.json
    467 Bytes
    Initial commit. 3 months ago