["Cinematic", "Photographic", "Anime", "Manga", "Digital art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model", “Painting”, “Animation” “Illustration”]

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.1-dev", torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('davidberenstein1957/image-preferences-flux-dev-lora', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('["Cinematic", "Photographic", "Anime", "Manga", "Digital art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model", “Painting”, “Animation” “Illustration”]').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]

data-is-better-together/open-image-preferences-v1-flux-dev-lora

Flux DreamBooth LoRA - data-is-better-together/image-preferences-flux-dev-lora

Model description

Trigger words