From my knowledge, this is the first community-uploaded DFloat11 compressed model on Hugging Face. For more information (including how to compress models yourself), check out https://huggingface.co/DFloat11 and https://github.com/LeanModels/DFloat11

Feel free to request for other models for compression as well, although I currently only know how to compress models based on the Flux architecture.

How to Use

diffusers

  1. Install the DFloat11 pip package (installs the CUDA kernel automatically; requires a CUDA-compatible GPU and PyTorch installed):

    pip install dfloat11[cuda12]
    # or if you have CUDA version 11:
    # pip install dfloat11[cuda11]
    
  2. To use the DFloat11 model, run the following example code in Python:

    import torch
    from diffusers import FluxPipeline
    from dfloat11 import DFloat11Model
    
    pipe = FluxPipeline.from_pretrained("shuttleai/shuttle-jaguar", torch_dtype=torch.bfloat16)
    pipe.enable_model_cpu_offload()
    
    DFloat11Model.from_pretrained('mingyi456/shuttle-jaguar-DF11', device='cpu', bfloat16_model=pipe.transformer)
    
    prompt = "A futuristic cityscape at sunset, with flying cars, neon lights, and reflective water canals"
    image = pipe(
        prompt,
        guidance_scale=0.0,
        num_inference_steps=4,
        max_sequence_length=256,
        generator=torch.Generator("cpu").manual_seed(0)
    ).images[0]
    image.save("shuttle-jaguar.png")
    

ComfyUI

Follow the instructions (have not tested myself) here: https://github.com/LeanModels/ComfyUI-DFloat11

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