Flux.2 [Klein] DreamBooth LoRA - Efradeca/lightloom-style-lora

Model description

These are Efradeca/lightloom-style-lora DreamBooth LoRA weights for black-forest-labs/FLUX.2-klein-base-4B.

The weights were trained using DreamBooth with the Flux2 diffusers trainer.

Quant training? None

Trigger words

You should use lghtlm style 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 AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.2", torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('Efradeca/lightloom-style-lora', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('lghtlm style').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]