Reddy V2

🚀 reddy-v2

reddy-v2是一个标准的PEFT LoRA，源自black-forest-labs/FLUX.1-dev，可用于文本到图像的生成任务。

🚀 快速开始

推理示例

以下是使用reddy-v2进行推理的示例代码：

import torch
from diffusers import DiffusionPipeline

model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'Unmapped2895/reddy-v2'
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
pipeline.load_lora_weights(adapter_id)

prompt = "Realistic wide shot photo of woman posing in a luxurious satin lingerie set, featuring a plunging bra, delicate thong and a classic garter belt with black stockings. The satin lingerie shimmers softly in the light, and the cut emphasizes both sophistication and a hint of allure. The lingerie is detailed with fine lace edges, highlighting her alluring figure. She elegantly styled hair as if getting ready for a formal event. The photo has a cinematic quality with rays of light and dramatic play of shadow and light"


## Optional: quantise the model to save on vram.
## Note: The model was quantised during training, and so it is recommended to do the same during inference time.
from optimum.quanto import quantize, freeze, qint8
quantize(pipeline.transformer, weights=qint8)
freeze(pipeline.transformer)
    
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
model_output = pipeline(
    prompt=prompt,
    num_inference_steps=20,
    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42),
    width=832,
    height=1216,
    guidance_scale=2.0,
).images[0]

model_output.save("output.png", format="PNG")

✨ 主要特性

• 基于black-forest-labs/FLUX.1-dev基础模型，通过PEFT LoRA技术进行微调。
• 支持文本到图像、图像到图像等多种生成任务。
• 训练过程中使用特定的验证提示和设置，确保生成图像的质量。

📚 详细文档

验证设置

• CFG：2.0
• CFG Rescale：0.0
• Steps：20
• Sampler：FlowMatchEulerDiscreteScheduler
• Seed：42
• Resolution：832x1216
• Skip-layer guidance：无

注意：验证设置不一定与训练设置相同。

你可以在以下图库中找到一些示例图像：

文本编码器未进行训练，推理时可复用基础模型的文本编码器。

训练设置

数据集

reddy - v2 - 512

• 重复次数：10
• 图像总数：13
• 纵横比桶总数：1
• 分辨率：0.262144兆像素
• 裁剪：否
• 裁剪风格：无
• 裁剪纵横比：无
• 是否用于正则化数据：否

reddy - v2 - 1024

• 重复次数：10
• 图像总数：5
• 纵横比桶总数：1
• 分辨率：1.048576兆像素
• 裁剪：否
• 裁剪风格：无
• 裁剪纵横比：无
• 是否用于正则化数据：否

📄 许可证

本项目使用其他许可证。