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
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]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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