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jayr23
/
jerome-v2

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

Instructions to use jayr23/jerome-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use jayr23/jerome-v2 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("jayr23/jerome-v2")
    
    prompt = "Medium portrait of jer0me man sitting in a cozy living room, holding a cup of coffee with a relaxed expression. Soft morning light streams in from a large window, creating gentle highlights. Shot on an 85mm lens, f/1.8, shallow depth of field, warm and inviting color grading, photorealistic."
    image = pipe(prompt).images[0]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
jerome-v2
246 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
jayr23's picture
jayr23
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  • sample
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  • .gitattributes
    3.49 kB
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  • README.md
    1.84 kB
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  • dataset.toml
    256 Bytes
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  • jerome-v2-000004.safetensors
    79.4 MB
    xet
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  • jerome-v2-000008.safetensors
    79.4 MB
    xet
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  • jerome-v2.safetensors
    79.4 MB
    xet
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  • sample_prompts.txt
    865 Bytes
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  • train.sh
    1.31 kB
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