FLUX_LoRA_adapter

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Flux Kontext DreamBooth LoRA - mingyu-oo/FLUX_HD_ES

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Model description

These are mingyu-oo/FLUX_HD_ES DreamBooth LoRA weights for black-forest-labs/FLUX.1-Kontext-dev.

The weights were trained using DreamBooth with the Flux diffusers trainer.

Was LoRA for the text encoder enabled? False.

Trigger words

You should use None to trigger the image generation.

Download model

Download the *.safetensors LoRA in the Files & versions tab.

Use it with the 🧨 diffusers library

from diffusers import FluxKontextPipeline
import torch
pipeline = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('mingyu-oo/FLUX_HD_ES', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('Designed by Hyundai, 3/4 front view, midsize sedan, three-box, balanced proportions, low stance, short overhangs, sleek beltline, clean body surfacing, angular shoulder lines, prominent grille, narrow intakes, sculpted hood, flush door handles, 19-inch multi-spoke wheels, low-profile tires, tinted glass, chrome accents, red paint').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

License

Please adhere to the licensing terms as described here.

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]