终极 FLUX.1 实用指南
6 个月前
FLUX.1 终极实用指南
学习使用 FLUX.1：埃隆·马斯克的 Grok 2 背后的无限图像生成器
作者
- Zijian Yang (ORCID: 0009–0006–8301–7634)
引言
在本文中，我们将逐步指导您如何使用 FLUX.1。
开源社区迎来了新的文本到图像生成模型 FLUX.1，继 SD 3 Medium 和 Kolors 之后。FLUX.1 由 Stability AI 的前核心成员开发，显著超越了 SD 3 的质量，甚至与闭源的 Midjourney v6.1 模型相媲美。这使得 FLUX.1 成为 AI 生成艺术的新基准，并为开源 AI 艺术的发展注入了新的动力。
FLUX.1 背后的公司是 Black Forest Labs，由 Stable Diffusion 的原始团队和几位 Stability AI 的前研究人员创立。与 Stability AI 一样，Black Forest Labs 致力于开发高质量的多模态模型并将其开源。该公司已经完成了 3100 万美元的种子融资。
Black Forest Labs 网站：https://blackforestlabs.ai/
FLUX.1 提供三个版本：Pro、Dev 和 Schnell。前两个模型的性能超过了主流模型如 SD3-Ultra，而较小的 FLUX.1 [schnell] 超越了 Midjourney v6.0 和 DALL·E 3 等更大模型。
FLUX.1 与主流模型的 ELO 分数比较
FLUX.1 在文本生成、遵循复杂指令和渲染人手方面表现出色。以下是其最强大模型 FLUX.1 [pro] 生成的图像示例。可以看到，即使在生成大块文本或多个角色时，文本或人手等细节也没有错误。
FLUX.1 [pro] 生成的图像示例
在线免费试用 FLUX.1
以下是一些可以在线体验 FLUX.1 模型的网站。如果您只是想探索并使用这个强大的文本到图像模型，免费在线访问是您最好的选择。
Hugging Face（免费 | 使用频率有限）
FLUX.1-dev:
https://huggingface.co/spaces/black-forest-labs/FLUX.1-dev
FLUX.1-schnell:
https://huggingface.co/spaces/black-forest-labs/FLUX.1-schnell
用户界面：
注意： 目前，FLUX.1 schnell 的使用限制较少，但在使用 FLUX.1 dev 生成多张图像后，您需要等待一段时间才能再次使用。
一幅高度详细且富有氛围的老年人肖像，站在一个磨损的乡村窗户旁。老人穿着一套磨损的深色西装，下面是一件微妙的格子衬衫，给人一种经典而庄重的外观。他的手中握着一个小物件，可能是打火机，手上有风霜的痕迹，显示出岁月的痕迹。他的表情严肃而沉思，深邃的皱纹和眼中流露出宁静的反思。光线柔和而散射，自然光透过窗户洒在他脸上和周围的老旧墙壁上，投下柔和的阴影。整体氛围怀旧而内省，捕捉了在简单而富有表现力的环境中孤独的瞬间。
fal.ai（免费 | $1 免费积分）
FLUX.1 schnell:
https://fal.ai/models/fal-ai/flux/schnell/playground
FLUX.1 dev:
https://fal.ai/models/fal-ai/flux/dev/playground
FLUX.1 pro:
https://fal.ai/models/fal-ai/flux-pro
登录 GitHub 后，您将获得 $1 的积分，这使您可以免费使用 FLUX.1 pro 20 次，FLUX.1 dev 40 次，或 FLUX.1 Schnell 333 次。
以下是 fal.ai 的定价表：
用户界面：
用户界面
一幅数字插图，电影海报标题为“寻找情绪”，是《海底总动员》的恶搞海报，描绘了一只抑郁的卡通小丑鱼，黑色的 emo 发型，眼线和穿孔，面无表情，游弋在黑暗的水下场景中，背景是电影标题以滴落的、粗糙的字体呈现，情绪化的蓝色和紫色调。
LiblibAI（免费 300 积分 | 中文网站）
LiblibAI 提供两种使用 FLUX.1 的方式，允许大约 15 次免费使用，使用提供的 300 积分。
方法 1：Web UI（每张图像消耗 20 积分）
目前，该网站提供四个版本：
- dev-fp8 版本：最推荐的版本，快速且稳定。
- dev 版本：也称为 fp16 版本，加载稍慢，容易出现内存不足。
- schnell 版本：涡轮版本，性能一般；不推荐使用。
- VAE 版本
使用 WEBUI 的推荐设置：
- 采样方法：仅支持 FlowMatchEuler。嵌入与 SD1.5 兼容，但可能与 SDXL 存在问题。
- CFG 官方推荐：3.5。
- 采样步骤：默认值为 20，可根据需要增加。
方法 2：ComfyUI（每张图像消耗 5 积分）
常规版本需要至少 32GB 的系统 RAM。测试显示，4090 GPU 可以完全占用其内存。推荐在本地使用 dev-fp8 版本。
用户界面：
一幅高度详细且逼真的年轻女性肖像，短发为柔和的粉色，造型为柔软的凌乱波浪。她穿着一件浅粉色 T 恤，上面印有醒目的红色文字“我爱你”。她在户外，背景是明亮、清澈的蓝天，远处可见海洋。光线柔和自然，给她的皮肤增添了柔和的光泽。她的表情沉思而宁静，目光投向远方，捕捉了一个平和而内省的瞬间。整体氛围生动而清新，色彩斑斓的头发增添了一丝奇幻感。
replicate（不免费）
https://replicate.com/black-forest-labs
replicate 提供三个 FLUX.1 模型：FLUX.1-dev、FLUX.1-pro 和 FLUX.1-schnell，均为付费。
定价表
用户界面：
一幅高度详细且富有想象力的独特鸡尾酒图像，装在一个高玻璃杯中，设计成水族箱的样子。饮料清澈，里面有冰块，杯中有模仿水下场景的元素：生机勃勃的绿色水生植物、鲜艳的橙色花朵和小装饰物，像鱼一样在饮料中游动。杯口装饰着一片薄薄的柠檬片，吸管优雅地放在饮料中。背景是一个昏暗的、温暖色调的酒吧，柔和的环境光营造出舒适的氛围。整体构图富有创意和奇幻感，将调酒艺术与富有表现力的水下主题相结合。
Flux AI 图像生成器（仅 FLUX.1 schnell 免费 | 100 免费积分）
https://fluxaiimagegenerator.com/
目前，仅提供 FLUX.1 schnell 版本的免费使用，免费生成的图像必须公开分享。注册后，您将获得 100 个免费积分，每天可使用 5 个积分。每生成一张图像消耗 1 个积分。
定价表
用户界面
一幅电视节目海报，标题为“打破面包”，玩弄著名节目《绝命毒师》的名字。海报上是一位面色严肃的面包师，穿着沾满面粉的围裙，手臂上搭着一个擀面杖，像武器一样。他站在一个乡村面包店的中央，周围是堆积的面包、糕点和面粉袋，所有这些都排列成模仿原始节目标志性沙漠背景的样子。在他身后，面包店的黑板菜单上列出了“肉桂卷卡特尔”和“蓝莓松饼毒品”等项目，暗示即将展开的烹饪混乱。面包师的表情严肃而滑稽，仿佛他即将用面团和决心征服世界。标题“打破面包”以粗体、风格化的文字显示在顶部，“打破”用粗糙、破裂的字体书写，而“面包”则用温暖、金色的字母书写，像新鲜出炉的面包。标语下方写着：“烘焙是一场危险的游戏”，增添了充满双关的幽默感。海报的整体色调是温暖的面包色调与原始节目中阴暗的色调的混合，将《绝命毒师》的紧张戏剧与“打破面包”的轻松烹饪扭曲结合在一起。
mystic（免费）
https://www.mystic.ai/black-forest-labs
提供 FLUX.1-pro、FLUX.1-dev 和 FLUX.1-schnell。
用户界面
详细、杰作、专业、鲜艳的色彩、令人惊叹的摄影，灵感来自 Jeremy Mann 和 Kelly McKernan，30mm 拍摄，动作场景，HDR，血源诅咒主题，史诗般的氛围，女性战士面对不可能的挑战，阴郁的维多利亚时代，手持宇宙注入的洛夫克拉夫特剑，女性化，灵感来自 Agnes Cecile，雕刻剑，蓝色光环，宇宙之眼。
安装 ComfyUI
官方 ComfyUI GitHub 仓库 提供了安装方法的基本指南，包括 Windows、Mac、Linux 和 Jupyter Notebook。
在本文中，我们将以 Windows 系统和 Nvidia GPU 为例，逐步演示安装和使用过程。
硬件要求
ComfyUI 官方仓库地址：ComfyUI 的 GitHub 仓库
您可以在仓库的 ReadMe 部分找到 直接下载链接 的蓝色链接，点击下载官方整理的集成包。
将集成包解压到您希望的本地目录以安装 ComfyUI。（我建议使用 7-Zip 来处理压缩文件）。解压后，文件目录应如下所示：
ComfyUI 目录说明：
ComfyUI_windows_portable
├── ComfyUI // Comfy UI 的主文件夹
│ ├── .git // Git 版本控制文件夹，用于代码版本管理
│ ├── .github // GitHub Actions 工作流文件夹
│ ├── comfy //
│ ├── 📁 comfy_extras //
│ ├── 📁 custom_nodes // ComfyUI 自定义节点文件的目录（插件安装目录）
│ ├── 📁 input // ComfyUI 上传文件夹，当您使用像加载图像这样的节点时，相应上传的图像将存储在此文件夹中
│ ├── 📁 models // 相应模型文件配置文件夹
│ | ├── 📁 checkpoints // 存储大型模型检查点文件的路径
│ | ├── 📁 clip // 存储 CLIP 文件的路径
│ | ├── 📁 clip_vision // 存储 CLIP_vision 文件的路径
│ | ├── 📁 configs
│ | ├── 📁 controlnet // 存储 ControlNet 模型文件的路径
│ | ├── 📁 diffusers
│ | ├── 📁 embedding // 存储嵌入模型文件的路径
│ | ├── 📁 gligen
│ | ├── 📁 hypernetworks // 存储超网络模型的路径
│ | ├── 📁 loras // 存储 Lora 模型文件的路径
│ | ├── 📁 style_models
│ | ├── 📁 unet
│ | ├── 📁 upscale_models // 存储放大模型文件的路径
│ | ├── 📁 vae // 存储 VAE 模型文件的路径
│ | └── 📁 vae_approx
│ ├── 📁 notebooks
│ ├── 📁 user // ComfyUI 用户信息（如配置文件、工作流信息等）
│ ├── 📁 output // ComfyUI 图像输出文件夹，当使用像保存图像这样的节点时，生成的图像将存储在此文件夹中
│ ├── extra_model_paths.yaml.example // 额外模型文件路径配置文件，如果您设置此项，请删除 .example 后缀并用文本编辑器编辑
│ └── ... // 其他文件
├── 📁 config // 配置文件夹
├── 📁 Python_embeded // 嵌入式 Python 文件
├── 📁 update
│ ├── update.py // ComfyUI 的 Python 脚本
│ ├── update_comfyUI.bat // ComfyUI 作者推荐的批处理命令，用于升级 ComfyUI
│ └── update_comfyui_and_python_dependencies.bat // 仅在您的 Python 依赖文件出现问题时运行此批处理命令
├── comfyui.log // Comfy UI 运行时日志文件
├── README_VERY_IMPORTANT.txt // README 文件，包括文件使用方法和说明等。
├── run_cpu.bat // 批处理文件，双击以在您的显卡为 A 卡或仅有 CPU 时启动 ComfyUI
└── run_nvidia_gpu.bat // 批处理文件，双击以在您的显卡为 N 卡（Nvidia）时启动 ComfyUI
让我们看看不同版本模型之间的差异，并下载我们需要的版本。
一幅高度详细且生动的年轻中国女性肖像，穿着传统汉服。她佩戴着精致华丽的银色头饰，上面装饰着复杂的花卉设计和与她服装相匹配的粉色花朵。她的头发优雅地梳成传统的发髻，柔和的发丝勾勒出她的脸庞。她面带温暖而优雅的微笑，妆容柔和自然，突显出她的青春美丽。她站在一片盛开的薰衣草田中，紫色的花朵营造出梦幻而浪漫的背景。阳光柔和地照耀着她的脸庞，为整体宁静而迷人的氛围增添了柔和的金色光辉。
FLUX.1 的不同版本
以下是对 FLUX.1 模型不同版本的详细介绍（本节旨在帮助您了解模型之间的差异；下一节将提供下载说明）
有关更多信息，请访问 FLUX.1 仓库：https://github.com/black-forest-labs/flux
详细、杰作、专业、鲜艳的色彩、令人惊叹的摄影，灵感来自 Jeremy Mann，30mm 拍摄，动作场景，HDR，公主桃子在沙丘车中竞速，逼真、粗犷、电影感、反乌托邦、真实的皮肤纹理、现实生活中，车头上写着“公主桃子”，镶嵌的文字，穿着公路皮衣，驾驶。
下载 FLUX.1 模型
您可以选择下载官方原始模型或量化模型。从以下选项中选择适合您需求的模型。
5 个主流 FLUX.1 模型版本
将下载的大型模型放入 ComfyUImodelsunet 目录。
- 如果您有 16GB 或更多的 VRAM，官方模型无疑是最佳选择，提供最佳性能和图像质量。
- 接下来是 FP8 模型，显著小于原始模型，可以在 8GB VRAM 上运行，关键文本和细节生成质量没有明显下降。
- 然后是 @lllyasviel 发布的 NF4 量化版本。这些模型更小，生成图像的速度更快。在 WebUI forge 中使用共享模式时，可以在 6GB VRAM 上运行。分为 v1 和 v2 两个版本，v2 提供更好的细节和速度。
- 最后是 @City96 开发的三个 GGUF 量化版本。Q8 版本在图像输出和速度上优于 FP8，需要超过 12GB 的 VRAM；Q4 版本可以在 8GB VRAM 上运行，并提供比 NF4 更好的生成质量。
- 注意：这些量化版本的使用许可证与原始模型一致，即 Dev 不用于商业用途，而 Schnell 可用于商业用途。
Kijai 的 FLUX.1 fp8 版本
对于大多数用户来说，顺利运行官方模型可能是一个挑战。在这里，我们可以使用其他作者优化的 FLUX.1 模型版本，以提供更好的体验。
https://huggingface.co/Kijai/flux-fp8/tree/main
在这里，我选择下载 FLUX.1 [schnell] fp8 进行测试。您可以根据需要下载模型。
- 下载
flux1-schnell-fp8.safetensors - 将下载的模型文件放入
ComfyUI/models/unet/文件夹
“fp”是什么意思？
量化是一种用于减少机器学习模型（特别是大型语言模型）大小和计算需求的技术。通过将高精度参数（如 32 位浮点数）转换为较低精度格式（如 8 位整数），量化有助于 减少内存使用并加速推理，而不会显著影响模型准确性。这一过程对于在资源受限的设备（如手机或边缘设备）上部署大型模型至关重要，使其能够实现更快、更高效的性能。量化通常在多个阶段中进行，包括训练后量化和量化感知训练，以实现模型效率和准确性之间的最佳平衡。
什么是 UNet 模型？
UNet 模型是一种卷积神经网络（CNN），主要用于图像分割，其目标是对图像中的每个像素进行分类。它具有对称的编码器-解码器结构：编码器通过逐步下采样输入图像来捕获上下文信息，而解码器通过上采样重建图像，精确到像素级细节。该模型的关键创新是使用跳跃连接，将编码器和解码器中对应的层连接起来，使其能够保留和结合高层次和低层次特征，这对于准确的分割和其他像素级预测任务至关重要。
威廉·莎士比亚坐在南伦敦南华克一座简朴的都铎时代房屋中，正用羽毛笔在烛光下写作，脸上流露出自信和满意的神情，确信自己正在写一部杰作（当然他确实如此），16 世纪末的英格兰，真实的历史细节。
下载 ComfyUI CLIP 模型
ComfyUI flux_text_encoders on hugging face
- 下载
clip_l.safetensors - 下载
t5xxl_fp8_e4m3fn.safetensors或t5xxl_fp16.safetensors，具体取决于您的 VRAM 和 RAM - 将下载的模型文件放入
ComfyUI/models/clip/文件夹。
注意：如果您之前使用过 SD 3 Medium，您可能已经拥有上述两个模型。
什么是 CLIP？
ComfyUI Clip 是一个基于阿里巴巴 M6 的开源预训练大型模型，专注于自然语言处理任务，如文本理解、代码分析和生成。在此上下文中，“语义分割”通常指模型理解和识别输入文本不同部分的能力，例如解析文档结构或识别代码块中的函数和变量名称等元素。ComfyUI Clip 利用深度学习技术高效提取文本中的关键信息，支持各种应用场景的定制任务。
CLIP（对比语言-图像预训练）是 OpenAI 于 2021 年发布的预训练视觉-语言模型。该模型通过无监督学习，从大量互联网图像和文本对中学习，使其能够理解图像内容并将其与自然语言描述关联，即使没有特定领域的标记数据。CLIP 模型的核心思想是将图像和文本映射到共享的高维向量空间，使得相似的文本描述和相应的图像在该空间中更接近。
在语义分割任务中，CLIP 可以作为特征提取器，根据文本描述为输入图像生成上下文相关的语义图。这一能力在图像理解和自动驾驶等领域非常有用。用户可以利用其跨模态能力来指导分割任务；例如，通过输入关于“猫”的文本，然后指导如何区分猫的脸与其他部分。
什么是 T5XXL？
T5XXL 是 Google 设计的文本到文本转换变换器（T5）模型的最大变体，适用于广泛的自然语言处理任务。拥有数十亿个参数，T5XXL 在翻译、摘要、问答、文本生成甚至代码补全等任务中表现出色，将所有任务框定为文本到文本问题。其庞大的规模使其能够捕捉语言中的复杂模式和细微差别，使其成为 T5 家族中最强大的模型之一。尽管其资源需求较高，T5XXL 在研究和工业界广泛应用于需要高准确性和复杂语言理解的应用，特别是在需要细致语言理解的领域。
宁静的池塘在竹林中，黎明时分，太阳刚刚开始露出地平线，熊猫在池塘边练习太极，透过晨露的薄雾，营造出大气透视，阳光照射下，它的动作优雅流畅——创造出和谐与平衡的感觉，池塘的平静水面反射出这一场景，邀请人们感受冥想与自然的连接，风格灵感来自 Howard Terpning 和 Jessica Rossier，lora:other/flux_realism_lora:1.0
下载 FLUX.1 VAE 模型
FLUX.1-schnell on hugging face
- 下载
ae.safetensors模型。 - 将下载的模型文件放入
ComfyUI/models/vae文件夹。 - 为了方便识别，您可以将其重命名为
flux_ae.safetensors；
什么是 VAE 模型？
变分自编码器（VAE）是一种深度学习模型，用于生成与给定数据集相似的新数据。它通过将输入数据压缩到表示为概率分布的低维潜在空间中，然后通过从该分布中采样重建原始数据。这使得 VAE 能够生成多样化的输出，适用于图像生成、数据插补和异常检测等任务。通过学习数据的潜在分布，VAE 可以以结构化和概率的方式生成新的相似数据点。
一幅惊艳的肖像，描绘了一位优雅的女性，穿着传统的华丽红金服饰。她有着长长的黑发，装饰着复杂的金色发饰。一条威严的红龙缠绕在她身边，龙头靠近她的肩膀，散发出一种力量和神秘感。龙的鳞片细致而闪亮，眼睛散发着强烈的绿色光芒。背景应为阴暗而情绪化的色调，强调场景的戏剧性和威严，女性的表情反映出冷静的自信。
在 ComfyUI 上运行 FLUX.1
在 ComfyUI_windows_portable 目录中，您可以看到两个文件 run_cpu.bat 和 run_nvidia_gpu.bat，您可以根据以下说明选择运行。
ComfyUI_windows_portable
├── ...其他文件省略
├── run_cpu.bat // 双击运行以在您的显卡为 A 卡或仅有 CPU 时启动 ComfyUI
└── run_nvidia_gpu.bat // 双击运行以在您的显卡为 N 卡（Nvidia）时启动 ComfyUI
如果您遇到以下错误：
PermissionError: [Errno 13] error while attempting to bind on address ('127.0.0.1', 8188): an attempt was made to access a socket in a way forbidden by its access permissions
您可以尝试以管理员权限打开 CMD 并执行以下命令：
net stop winnat
net start winnat
然后再次运行启动脚本。
如上图所示，当您看到“要查看 GUI，请访问：http://127.0.0.1:8188”
这意味着 ComfyUI 已成功启动。如果浏览器未正常启动，您可以直接通过浏览器访问“要查看 GUI，请访问：”后面的链接，例如上面的示例，应为 http://127.0.0.1:8188。
打开的网页如下：
这是默认工作流。让我们暂时保持网页打开，不关闭任何内容，继续进行下一步。
一位25岁的年轻女性，肤色黝黑，五官深邃，站在雨中的桥上，背景是赛博朋克城市景观，穿着黑色高领衫和蓝色飞行员夹克，白色牛仔裤，周围有绿色和橙色的飞溅，角色周围有粗线条。
选择 FLUX.1 ComfyUI 工作流示例
在 ComfyUI 中构建工作流是一个需要大量时间和学习的过程。如果您更喜欢更直接和现成的体验，使用模板是最佳选择。本文不会深入探讨如何构建工作流，但会提供一些您可以直接运行的示例。
从下面选择您需要的工作流示例，复制代码并将其保存为 json 文件（您可以将其粘贴到 txt 文件中，保存后将文件扩展名从 txt 更改为 json）。如果您不确定选择哪个，可以选择第一个。
返回到您之前打开的工作流界面网页（如果您还没有打开，请参考前面的部分）。在主界面上，点击右侧的 load 按钮以加载工作流文件。
稍后在文章中，我们还将包括 LoRA 和 ControlNet 的现成工作流。
在此处查找更多工作流示例：https://openart.ai/workflows/all?keyword=flux
FLUX.1 Dev ComfyUI 工作流示例
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t5xxl_fp16.safetensors and clip_l.safetensors go in: ComfyUI/models/clip/
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FLUX.1 Schnell ComfyUI 工作流示例
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加载工作流后，界面如下所示：
请注意，工作流模板中的配置可能与您的实际设置不同。仔细检查并编辑左侧图像中“加载扩散模型”、“DualCLIPLoader”和“加载 VAE”部分的模型选择信息，以确保您使用的是刚下载的版本。
在右侧的绿色框中输入您的提示，然后点击浮动工具栏上的“排队提示”以开始生成图像。如果出现任何错误，请检查变红的节点配置以确保它们正确。
此时，您可以使用各种版本的 FLUX 模型生成图像。以下是使用 FLUX Schnell FP8 模型生成的图像示例：
一幅超现实的场景，一名男子骑在鲨鱼背上，快速穿越海洋。男子一边吃汉堡，一边抓住鲨鱼。视角应为望远镜，给场景一种遥远、放大的感觉。海洋广阔，波涛汹涌，天空晴朗明亮，增添了这一不寻常而冒险的时刻的对比。
双重曝光照片，呈现出脆弱的蝴蝶形状和形式，背景是抽象的超现实主义风景。翅膀以生动、逼真的细节呈现，细腻的脉络和标记在风景的旋涡和线条中清晰可见。风景本身具有梦幻般的特质，色彩和形状的旋涡既混乱又迷人。
LoRA（高级用法）
以下是一个可以在线体验 FLUX.1 LoRA 模型的网站：
https://huggingface.co/spaces/multimodalart/flux-lora-the-explorer
LoRA（低秩适应）用于文本到图像生成，以较少的计算成本微调大型预训练模型，如 Stable Diffusion。通过仅修改模型参数的小部分低秩子集，LoRA 使模型能够根据提供的文本提示适应特定的风格、主题或领域，而无需重新训练整个模型。
假设您有一个预训练的文本到图像模型，您希望它生成特定艺术风格的图像，例如“梵高风格的风景”。您可以使用 LoRA 在一小部分与梵高风格图像配对的相关文本描述的数据集上微调模型，而不是重新训练整个模型，这将消耗大量资源。这使得模型能够学习该风格的细微差别，并将其应用于新的文本提示，生成具有所需艺术特征的图像。
下载 LoRA 模型
FLUX.1 LoRA 和其他资源，您可以在以下网站下载：
在这里，我们选择 XLabs-AI 团队创建的 LoRA：
https://huggingface.co/XLabs-AI/flux-lora-collection/tree/main
目前，XLabs 已发布 7 个 FLUX.1 的 LoRA 模型，包括动漫、艺术、迪士尼、MJV6、毛绒、现实主义和风景。下载所需的 LoRA 模型文件，并将其放入 ComfyUImodelsloras 目录。
对于没有
comfy_converted的 LoRA 模型，您需要安装x-flux-comfyui插件，并将其放入ComfyUI/models/xlabs/loras目录以使用。
LoRA 工作流
在 ComfyUI 中使用 FLUX.1 LoRA 时，还有两种不同的工作流可用：一种基于本地工作流，主要模型存储在 Unet 文件夹中；另一种是适用于 ComfyUI 发布的 fp8 模型的简化工作流，主要模型存放在检查点文件夹中。
本地工作流：
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此工作流需要使用 https://github.com/pythongosssss/ComfyUI-Custom-Scripts。
将仓库克隆到您的 ComfyUI custom_nodes 目录：git clone https://github.com/pythongosssss/ComfyUI-Custom-Scripts.git。该脚本将自动安装所有自定义脚本和节点。它将尝试使用符号链接和连接点，以避免复制文件并保持其最新。
克隆后，重启 ComfyUI 以使更改生效。
推荐阅读：
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