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Runware
/
flux_fill_onereward

Diffusers
Safetensors
FluxFillPipeline
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Diffusers

    How to use Runware/flux_fill_onereward with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import FluxFillPipeline
    from diffusers.utils import load_image
    
    image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
    mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")
    
    # switch to "mps" for apple devices
    pipe = FluxFillPipeline.from_pretrained("Runware/flux_fill_onereward", dtype=torch.bfloat16, device_map="cuda")
    image = pipe(
        prompt="a white paper cup",
        image=image,
        mask_image=mask,
        height=1632,
        width=1232,
        guidance_scale=30,
        num_inference_steps=50,
        max_sequence_length=512,
        generator=torch.Generator("cpu").manual_seed(0)
    ).images[0]
    image.save(f"flux-fill-dev.png")
  • Notebooks
  • Google Colab
  • Kaggle
flux_fill_onereward / text_encoder
246 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
Washakh's picture
Washakh
Upload folder using huggingface_hub
d6d8050 verified 11 months ago
  • config.json
    555 Bytes
    Upload folder using huggingface_hub 11 months ago
  • model.safetensors
    246 MB
    xet
    Upload folder using huggingface_hub 11 months ago