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S1T4L
/
Zero123pp_custom

Image-to-Image
Diffusers
Zero123PlusPipeline
art
Model card Files Files and versions
xet
Community

Instructions to use S1T4L/Zero123pp_custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use S1T4L/Zero123pp_custom with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    from diffusers.utils import load_image
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("S1T4L/Zero123pp_custom", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Turn this cat into a dog"
    input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
    
    image = pipe(image=input_image, prompt=prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
Zero123pp_custom
3.85 GB
Ctrl+K
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  • 1 contributor
History: 14 commits
S1T4L's picture
S1T4L
Upload inference.py
e3be4fb verified about 2 years ago
  • feature_extractor_clip
    Upload 19 files about 2 years ago
  • feature_extractor_vae
    Upload 19 files about 2 years ago
  • scheduler
    Upload 19 files about 2 years ago
  • text_encoder
    Upload 19 files about 2 years ago
  • tokenizer
    Upload 19 files about 2 years ago
  • unet
    Upload 19 files about 2 years ago
  • vae
    Upload 19 files about 2 years ago
  • vision_encoder
    Upload 19 files about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    894 Bytes
    Update README.md about 2 years ago
  • inference.py
    15.4 kB
    Upload inference.py about 2 years ago
  • model_index.json
    2.62 kB
    Update model_index.json about 2 years ago