Model description for Flux-Super-Portrait-LoRA

Image Gallery

Image Processing Parameters

Parameter	Value	Parameter	Value
LR Scheduler	constant	Noise Offset	0.03
Optimizer	AdamW	Multires Noise Discount	0.1
Network Dim	64	Multires Noise Iterations	10
Network Alpha	32	Repeat & Steps	17 & 2650
Epoch	14	Save Every N Epochs	1

Labeling: florence2-en(natural language & English)

Total Images Used for Training : 19 [ Flat 4K ]

Best Dimensions & Inference

Dimensions	Aspect Ratio	Recommendation
1280 x 832	3:2	Best
1024 x 1024	1:1	Default

Inference Range

• Recommended Inference Steps: 30–35

Setting Up

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/Flux-Super-Portrait-LoRA"
trigger_word = "Super Portrait"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

Trigger words

You should use Super Portrait to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.