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HomeLLMsAWPortrait FL

AWPortrait FL

by Shakker-Labs

Open source · 8k downloads · 490 likes

3.4
(490 reviews)ImageAPI & Local
About

AWPortrait FL is an AI model specialized in generating portrait images, fine-tuned from FLUX.1-dev using a high-quality dataset. It excels in composition, detail, and realism, particularly in skin and textures, delivering more refined and natural results than its base model. Designed for fashion photography, it is especially suited for creators aiming to produce aesthetic and professional portraits. What sets it apart is its ability to generate highly visually precise images while remaining accessible through optimized versions like LoRA to reduce memory usage.

Documentation

AWPortrait-FL

AWPortrait-FL is finetuned on FLUX.1-dev using the training set of AWPortrait-XL and nearly 2,000 fashion photography photos with extremely high aesthetic quality. It has remarkable improvements in composition and details, with more delicate and realistic skin and textual. Trained by DynamicWang at AWPlanet.

Comparison

The following example shows a simple comparison with FLUX.1-dev under the same parameter setting.

Inference

Python
import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("Shakker-Labs/AWPortrait-FL", torch_dtype=torch.bfloat16)
pipe.to("cuda")

prompt = "close up portrait, Amidst the interplay of light and shadows in a photography studio,a soft spotlight traces the contours of a face,highlighting a figure clad in a sleek black turtleneck. The garment,hugging the skin with subtle luxury,complements the Caucasian model's understated makeup,embodying minimalist elegance. Behind,a pale gray backdrop extends,its fine texture shimmering subtly in the dim light,artfully balancing the composition and focusing attention on the subject. In a palette of black,gray,and skin tones,simplicity intertwines with profundity,as every detail whispers untold stories."

image = pipe(prompt, 
             num_inference_steps=24, 
             guidance_scale=3.5,
             width=768, height=1024,
            ).images[0]
image.save(f"example.png")

LoRA Inference

To save memory, we also add a LoRA version to achieve same performance.

Python
import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights('Shakker-Labs/AWPortrait-FL', weight_name='AWPortrait-FL-lora.safetensors')
pipe.fuse_lora(lora_scale=0.9)
pipe.to("cuda")

prompt = "close up portrait, Amidst the interplay of light and shadows in a photography studio,a soft spotlight traces the contours of a face,highlighting a figure clad in a sleek black turtleneck. The garment,hugging the skin with subtle luxury,complements the Caucasian model's understated makeup,embodying minimalist elegance. Behind,a pale gray backdrop extends,its fine texture shimmering subtly in the dim light,artfully balancing the composition and focusing attention on the subject. In a palette of black,gray,and skin tones,simplicity intertwines with profundity,as every detail whispers untold stories."

image = pipe(prompt, 
             num_inference_steps=24, 
             guidance_scale=3.5,
             width=768, height=1024,
            ).images[0]
image.save(f"example.png")

Online Inference

You can also download this model at Shakker AI, where we provide an online interface to generate images.

Acknowledgements

This model is trained by our copyrighted users DynamicWang. We release this model under permissions. The model follows flux-1-dev-non-commercial-license and the generated images are also non commercial.

Capabilities & Tags
diffuserssafetensorstext-to-imagestable-diffusionimage-generationfluxenendpoints_compatible
Links & Resources
Specifications
CategoryImage
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Rating
3.4

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