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TheMindExpansionNetwork
/
pip3-dream

Text-to-Image
Diffusers
flux
lora
template:sd-lora
fluxgym
Model card Files Files and versions
xet
Community

Instructions to use TheMindExpansionNetwork/pip3-dream with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use TheMindExpansionNetwork/pip3-dream 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("TheMindExpansionNetwork/pip3-dream")
    
    prompt = "\"pip3, a meticulously hand-drawn pipe rendered in pencil and ink, heavy cross-hatching and strong contrast on a white background, subtle dreamlike shadows, text near the bottom: 'Ceci n'est pas une pipe...'\""
    image = pipe(prompt).images[0]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
pip3-dream
200 MB
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  • 1 contributor
History: 2 commits
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TheMindExpansionNetwork
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  • sample
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  • .gitattributes
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  • README.md
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  • dataset.toml
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  • pip3-dream-000004.safetensors
    39.8 MB
    xet
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  • pip3-dream-000008.safetensors
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  • pip3-dream-000012.safetensors
    39.8 MB
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  • pip3-dream.safetensors
    39.8 MB
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  • sample_prompts.txt
    1.1 kB
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  • train.sh
    1.38 kB
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