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joseplcam
/
Qwen-Image-2.1-NVFP4

Text-to-Image
Diffusers
Safetensors
QwenImage21Pipeline
qwen-image
qwen-image-2.1
nvfp4
svdquant
nunchaku
blackwell
image-editing
8-bit precision
Model card Files Files and versions
xet
Community

Instructions to use joseplcam/Qwen-Image-2.1-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use joseplcam/Qwen-Image-2.1-NVFP4 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("joseplcam/Qwen-Image-2.1-NVFP4", 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
Qwen-Image-2.1-NVFP4 / text_encoder
11.8 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
joseplcam's picture
joseplcam
Inline kernel setup: Diffusers downloads only each component's own module
c10a8f8 verified 3 days ago
  • config.json
    6.37 kB
    Replace with SVDQuant+GPTQ NVFP4 DiT and text encoder, native in Diffusers 3 days ago
  • generation_config.json
    213 Bytes
    Qwen-Image-2.1 NVFP4 DiT + NVFP4 Qwen3-VL encoder for SGLang Diffusion 4 days ago
  • model.safetensors
    11.8 GB
    xet
    Replace with SVDQuant+GPTQ NVFP4 DiT and text encoder, native in Diffusers 3 days ago
  • modeling_nunchaku_qwen3vl.py
    3.49 kB
    Inline kernel setup: Diffusers downloads only each component's own module 3 days ago