Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

Gemneye
/
UnFlux

Text-to-Image
Diffusers
lora
template:diffusion-lora
Model card Files Files and versions
xet
Community

Instructions to use Gemneye/UnFlux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use Gemneye/UnFlux with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
    pipe.load_lora_weights("Gemneye/UnFlux")
    
    prompt = "Ultra high-resolution close-up portrait of a man, full face in frame, hyperrealistic skin texture with microscopic facial details. Visible pores, subtle microveins, fine skin imperfections and natural tone variation. Sharp and vibrant eyes with detailed irises, realistic eyelashes and eyebrows. Balanced lighting with minimal gloss on nose and forehead, avoiding oily appearance. Realistic subsurface scattering, soft shadows, 4K, 8K, photorealism, cinematic quality, super resolution"
    image = pipe(prompt).images[0]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
UnFlux
345 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Gemneye's picture
Gemneye
Update README.md
ae51c0d verified 9 months ago
  • images
    Add 2 files 9 months ago
  • .gitattributes
    2.31 kB
    initial commit 9 months ago
  • README.md
    1.01 kB
    Update README.md 9 months ago
  • unflux_v1.safetensors
    344 MB
    xet
    Add 2 files 9 months ago