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--- |
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license: other |
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license_name: bespoke-lora-trained-license |
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license_link: https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=RentCivit&allowDerivatives=False&allowDifferentLicense=False |
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tags: |
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- text-to-image |
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- stable-diffusion |
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- lora |
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- diffusers |
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- template:sd-lora |
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- migrated |
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- celebrity |
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base_model: black-forest-labs/FLUX.1-dev |
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--- |
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# Mckenna Grace, 768 portrait |
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<Gallery /> |
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([CivitAI](https://civitai.com/models/)) |
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## Model description |
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<p>Specially for portraits and closeup portraits. Selected eyes look at camera. HD and sharp images selected to dataset. Used 100-150 photos.</p><p>Trained on Comfyui FluxTrainer on 16gb Vram</p><p>Better use resolution 768 (minimize face-body proportion distortions) and than upscale whatever you want.</p><p>Small size of LORA because of training only 2 blocks: 7 and 20.</p><p>Top line of the GRID is this checkpoint. Grids for lora strength 0.8 and 1.2</p> |
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## Download model |
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Weights for this model are available in Safetensors format. |
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[Download](/Keltezaa/mckenna-grace-768-portrait/tree/main) them in the Files & versions tab. |
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) |
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```py |
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from diffusers import AutoPipelineForText2Image |
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import torch |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device) |
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pipeline.load_lora_weights('Keltezaa/mckenna-grace-768-portrait', weight_name='mckenna_768_rank128_bf16-step03500.safetensors') |
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image = pipeline('Your custom prompt').images[0] |
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``` |
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters) |
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