🚀 AWPortrait-FL

AWPortrait-FL是一款文本到图像的模型，基于FLUX.1-dev进行微调。它使用了AWPortrait-XL的训练集以及近2000张具有极高美学品质的时尚摄影照片进行训练。该模型在构图和细节方面有显著提升，能够生成皮肤和纹理更加细腻逼真的图像。

🚀 快速开始

模型推理

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推理

为了节省内存，我们还提供了LoRA版本以实现相同的性能。

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")

在线推理

你也可以在Shakker AI下载此模型，我们在该平台提供了在线图像生成界面。

✨ 主要特性

• 微调优化：基于FLUX.1-dev进行微调，使用了高质量的训练数据，在构图和细节上有显著提升。
• 效果出色：生成的图像皮肤和纹理更加细腻逼真。
• 节省内存：提供LoRA版本，可在节省内存的同时实现相同性能。

📦 模型信息

📄 许可证

本模型遵循flux-1-dev-non-commercial-license，生成的图像也仅可用于非商业用途。该模型由我们拥有版权的用户DynamicWang训练，并在获得许可的情况下发布。

🔍 对比展示

以下示例展示了在相同参数设置下，与FLUX.1-dev的简单对比。

🖼️ 模型展示

海报展示

封面展示