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collinhead
/
heathcliff

Text-to-Image
Diffusers
StableDiffusionPipeline
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Diffusers

    How to use collinhead/heathcliff with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("collinhead/heathcliff", 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
  • Local Apps
  • Draw Things
  • DiffusionBee
heathcliff
7.75 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
collinhead's picture
collinhead
Create model.yaml
9c1f692 about 3 years ago
  • samples
    Upload 18 files about 3 years ago
  • scheduler
    Upload 18 files about 3 years ago
  • text_encoder
    Upload 18 files about 3 years ago
  • tokenizer
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  • unet
    Upload 18 files about 3 years ago
  • vae
    Upload 18 files about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    28 Bytes
    initial commit about 3 years ago
  • args.json
    4.44 kB
    Upload 18 files about 3 years ago
  • model.ckpt

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.HalfStorage"

    What is a pickle import?

    2.58 GB
    xet
    Upload 18 files about 3 years ago
  • model.yaml
    1.79 kB
    Create model.yaml about 3 years ago
  • model_index.json
    517 Bytes
    Upload 18 files about 3 years ago