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NadaGh
/
working

Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Diffusers

    How to use NadaGh/working with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("NadaGh/working", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "tst chair"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Draw Things
  • DiffusionBee
working / diffusers /docs /source /ko /using-diffusers
215 kB
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  • 1 contributor
History: 1 commit
NadaGh's picture
NadaGh
End of training
dde5d93 verified almost 2 years ago
  • conditional_image_generation.md
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  • controlling_generation.md
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  • custom_pipeline_overview.md
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  • depth2img.md
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  • diffedit.md
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  • img2img.md
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  • kandinsky.md
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  • loading.md
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  • other-formats.md
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  • push_to_hub.md
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  • schedulers.md
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  • sdxl_turbo.md
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  • stable_diffusion_jax_how_to.md
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  • svd.md
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  • textual_inversion_inference.md
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  • unconditional_image_generation.md
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  • weighted_prompts.md
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  • write_own_pipeline.md
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