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mingyi456/shuttle-jaguar-DF11
shuttle-jaguar-DF11 is a text-to-image model from mingyi456. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as apache-2.0.
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:…
Downloads · 30 days
26
41% of all-time downloads
All-time downloads
64
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.safetensors16.3 GB · 100%
How the weights are stored.
U816.2B · 100%
From the Hugging Face model README
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.
diffusersInstall 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")
Follow the instructions (have not tested myself) here: https://github.com/LeanModels/ComfyUI-DFloat11