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CompVis
/
ldm-celebahq-256

Unconditional Image Generation
Diffusers
PyTorch
LDMPipeline
Model card Files Files and versions
xet
Community
7

Instructions to use CompVis/ldm-celebahq-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use CompVis/ldm-celebahq-256 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("CompVis/ldm-celebahq-256", 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
ldm-celebahq-256
1.32 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 30 commits
david20571015's picture
david20571015
Update vqvae/config.json
f02a066 verified over 2 years ago
  • images
    Move images almost 4 years ago
  • scheduler
    [Celeba-256] Upload first model almost 4 years ago
  • unet
    convert weights almost 4 years ago
  • vqvae
    Update vqvae/config.json over 2 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • README.md
    4.33 kB
    Update README.md almost 4 years ago
  • model_index.json
    228 Bytes
    Update model_index.json almost 4 years ago
  • run.py
    2.24 kB
    update config almost 4 years ago