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