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ajh-code
/
Mage-Flow-NVFP4-Quality-AJH

Text-to-Image
Diffusers
Safetensors
MageFlowPipeline
ajh
mage-flow
mage-flow-nvfp4-quality-ajh
nvfp4
blackwell
qwen3-vl
quantization
quality
Model card Files Files and versions
xet
Community

Instructions to use ajh-code/Mage-Flow-NVFP4-Quality-AJH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use ajh-code/Mage-Flow-NVFP4-Quality-AJH with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("ajh-code/Mage-Flow-NVFP4-Quality-AJH", torch_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 Settings
  • Draw Things
  • DiffusionBee
Mage-Flow-NVFP4-Quality-AJH / runtime
1.5 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
ajh-code's picture
ajh-code
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5cc2385 verified 5 days ago
  • libmage_nvfp4_linear.so
    1.19 MB
    xet
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  • libmage_nvfp4_torch_op.so
    167 kB
    xet
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  • nvfp4_linear.cu
    40.8 kB
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  • nvfp4_linear.h
    2.23 kB
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  • packed_artifact.py
    40.7 kB
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  • packed_nvfp4_linear.py
    17.5 kB
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  • quant_text_encoder.py
    13.5 kB
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  • sm120_linear_op.cpp
    12.2 kB
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  • standard_transformer.py
    10 kB
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  • torch_ops_native.py
    7.98 kB
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