Mani Flux Dress

🚀 mani - flux - dress

这是一个基于[black - forest - labs/FLUX.1 - dev](https://huggingface.co/black - forest - labs/FLUX.1 - dev)的LyCORIS适配器。它可用于特定风格的图像生成，在时尚摄影场景图像生成方面具有一定优势。

🚀 快速开始

推理示例

import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights


def download_adapter(repo_id: str):
    import os
    from huggingface_hub import hf_hub_download
    adapter_filename = "pytorch_lora_weights.safetensors"
    cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
    cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
    path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
    path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
    os.makedirs(path_to_adapter, exist_ok=True)
    hf_hub_download(
        repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
    )

    return path_to_adapter_file
    
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_repo_id = 'PixelWormhole/mani-flux-dress'
adapter_filename = 'pytorch_lora_weights.safetensors'
adapter_file_path = download_adapter(repo_id=adapter_repo_id)
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
wrapper.merge_to()

prompt = "A film still of a high fashion photoshoot featuring the _8FSL39XP1_ Dress, an elegant off-the-shoulder design in delicate white lace with floral motifs. The dress is form-fitting, mini-length, with long sleeves that flare slightly at the cuffs. The scene is set in a luxurious, modern Mediterranean architectural space with a sea view. A beautiful, young, natural-looking European woman with long hair is captured in a dynamic mid-motion pose, either mid-step or gently turning. She stands against a backdrop of clean white stone and curated designer furniture in neutral tones, with the calm, open sea visible in the distance. Her expression is serene and self-assured, her posture poised and refined. Natural daylight enhances the soft textures and casts gentle shadows across the scene. The color palette blends creamy whites, stone beiges, and hints of ocean blue."


## Optional: quantise the model to save on vram.
## Note: The model was not quantised during training, so it is not necessary to quantise it 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=28,
    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42),
    width=1024,
    height=1024,
    guidance_scale=3.0,
).images[0]

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

✨ 主要特性

• 基于LyCORIS技术，可有效适配基础模型，提升特定场景的图像生成效果。
• 支持多种推理设置，可灵活调整以满足不同需求。

📚 详细文档

验证设置

• CFG：3.0
• CFG Rescale：0.0
• 步数：28
• 采样器：FlowMatchEulerDiscreteScheduler
• 随机种子：42
• 分辨率：1024x1024
• 跳过层引导：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。你可以在推理时重用基础模型的文本编码器。

训练设置

LyCORIS配置

{
    "algo": "lora",
    "multiplier": 1.0,
    "linear_dim": 64,
    "linear_alpha": 32,
    "apply_preset": {
        "target_module": [
            "Attention",
            "FeedForward"
        ],
        "module_algo_map": {
            "Attention": {
                "factor": 16
            },
            "FeedForward": {
                "factor": 8
            }
        }
    }
}

数据集

📄 许可证

许可证类型：other