par linoyts
Open source · 5k downloads · 26 likes
Le modèle Flux2 Klein Delight LoRA est une version fine-tunée de Flux.2-klein-base-9B, spécialement conçue pour générer des images de haute qualité à partir de descriptions textuelles. Il utilise la technique DreamBooth pour affiner les capacités du modèle de base, offrant des rendus plus précis et stylisés. Ce modèle se distingue par sa capacité à produire des images détaillées et cohérentes, idéales pour des applications créatives comme l’art numérique ou la conception visuelle. Son déclencheur neutre ("None") permet une utilisation intuitive sans mots-clés spécifiques. Il est particulièrement adapté aux utilisateurs cherchant à exploiter la puissance de Flux.2 dans des projets personnalisés avec un minimum de contraintes techniques.
These are linoyts/Flux2-Klein-Delight-LoRA DreamBooth LoRA weights for black-forest-labs/FLUX.2-klein-base-9B.
The weights were trained using DreamBooth with the Flux2 diffusers trainer.
FP8 training? True
You should use None to trigger the image generation.
Download the *.safetensors LoRA in the Files & versions tab.
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('linoyts/Flux2-Klein-Delight-LoRA', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('Relight the image to remove all existing lighting conditions and replace them with neutral, uniform illumination. Apply soft, evenly distributed lighting with no directional shadows, no harsh highlights, and no dramatic contrast. Maintain the original identity of all subjects exactly—preserve facial structure, skin tone, proportions, expressions, hair, clothing, and textures. Do not alter pose, camera angle, background geometry, or image composition. Lighting should appear balanced, and studio-neutral, similar to diffuse overcast or a soft lightbox setup. Ensure consistent exposure across the entire image with realistic depth and subtle shading only where necessary for form.').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
Please adhere to the licensing terms as described here.
# TODO: add an example code snippet for running this diffusion pipeline
[TODO: provide examples of latent issues and potential remediations]
[TODO: describe the data used to train the model]