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britmob
/
nhrl_uncoditional

Diffusers
TensorBoard
Safetensors
DDPMPipeline
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Diffusers

    How to use britmob/nhrl_uncoditional with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("britmob/nhrl_uncoditional", 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
nhrl_uncoditional
18.7 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 98 commits
britmob's picture
britmob
Epoch 150
38cf4f8 over 2 years ago
  • checkpoint-1000
    Epoch 50 over 2 years ago
  • checkpoint-1500
    Epoch 100 over 2 years ago
  • checkpoint-2000
    Epoch 100 over 2 years ago
  • checkpoint-2500
    Epoch 100 over 2 years ago
  • checkpoint-3000
    Epoch 150 over 2 years ago
  • checkpoint-3500
    Epoch 150 over 2 years ago
  • checkpoint-4000
    Epoch 580 over 2 years ago
  • checkpoint-4500
    Epoch 650 over 2 years ago
  • checkpoint-500
    Epoch 50 over 2 years ago
  • checkpoint-5000
    Epoch 720 over 2 years ago
  • logs
    Epoch 150 over 2 years ago
  • scheduler
    Epoch 0 over 2 years ago
  • unet
    Epoch 150 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • model_index.json
    186 Bytes
    Epoch 0 over 2 years ago