ComfyUI-TrainTools-MZ
Nodes for fine-tuning lora in ComfyUI, dependent on training tools such as kohya-ss/sd-scripts
Nodes (18)
The deepspeed-flavored tuning node for native Hunyuan DiT training
Feed it images once, let it skip the reruns
The native Hunyuan DiT path starts by cloning Tencent's own repo
A full Hunyuan DiT sampler as one node, with auto-downloaded weights
Auto-downloads weights, needs deepspeed by hand
The dataset copier that's secretly the same node as KohyaSSDatasetConfig
Every Kohya tuning knob, dumped into one node (network_dim and friends)
Training a ControlNet in ComfyUI — with the preprocessing already in the graph
Turns a ComfyUI image batch into a Kohya-ready training set
This node quietly installs Kohya inside your ComfyUI (that's the point)
The Hunyuan DiT workspace starter that clones KohakuBlueleaf's fork instead
The Hunyuan DiT LoRA trainer via KohakuBlueleaf's Kohya fork
Generate with your trained Hunyuan DiT LoRA, right inside the same graph
The one MinusZone train node you should actually use now
The old training main thread — where Kohya actually runs inside ComfyUI
One template JSON, then tweak
Images from a folder path, straight into a batch
Pretty-print any config object in your graph
ComfyUI-TrainTools-MZ
在ComfyUI中进行lora微调的节点,依赖于kohya-ss/sd-scripts等训练工具(Nodes for fine-tuning lora in ComfyUI, dependent on training tools such as kohya-ss/sd-scripts)
Recent changes
[20240706] 支持混元lora训练,脚本来自https://github.com/KohakuBlueleaf/sd-scripts/tree/HunYuanDiT 分支
Installation
- Clone this repo into
custom_nodesfolder. - Restart ComfyUI.
Nodes
MZ_KohyaSS_KohakuBlueleaf_HYHiDInitWorkspace | MZ_KohyaSS_KohakuBlueleaf_HYHiDLoraTrain
MZ_KohyaSSInitWorkspace
初始化训练文件夹,文件夹位于output目录(Initialize the training folder, the folder in the output directory)
- lora_name(LoRa名称): 用于生成训练文件夹的名称(Used to generate the name of the training folder
- branch(分支): sd-scripts的分支,默认为当前代码调试时使用的分支(sd-scripts branch, default is the branch used when debugging the current code)
- source(源): sd-scripts的源,默认为github,下载有问题的话可以切换加速源(sd-scripts source, default is github, if there is a problem with the download, you can switch to the accelerated source)
MZ_ImagesCopyWorkspace
复制图片到训练文件夹中和一些数据集配置(Copy images to the training folder and some dataset configurations)
- images(图片列表): 推荐使用 https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite 中的上传文件夹节点 (It is recommended to use the upload folder node in https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite )
- force_clear(强制清空): 复制图片前是否强制清空原有文件夹内容(Whether to force clear the original folder content before copying the image)
- force_clear_only_images(仅清空图片): 仅清空图片文件夹内容,不清空其他文件夹内容(Only clear the content of the image folder, not the content of other folders)
- same_caption_generate(生成相同标注): 是否生成相同的标注文件(Whether to generate the same annotation file)
- same_caption(单一标签): 生成相同标签的内容(Generate content with the same label)
- 其他字段参考: https://github.com/kohya-ss/sd-scripts
MZ_KohyaSSUseConfig
一些基础的训练配置(Some basic training configurations)
- 没什么特殊的,字段参考: https://github.com/kohya-ss/sd-scripts
MZ_KohyaSSAdvConfig
更多的训练配置(More training configurations)
- 没什么特殊的,字段参考: https://github.com/kohya-ss/sd-scripts
MZ_KohyaSSTrain
训练主线程(Training main thread)
- base_lora(基础lora): 加载一个lora模型后进行训练,和sd-scripts中的
network_weights参数一致,启用时忽略dim/alpha/dropout(Train after loading a lora model, consistent with thenetwork_weightsparameter in sd-scripts, ignore dim/alpha/dropout when enabled) - sample_generate(启用样图生成): 每次保存模型时进行一次示例图片生成,并展示训练过程中每个保存epoch时的示例图片(Enable example image generation each time the model is saved, and display the example image at each saved epoch during training)
- sample_prompt(提示词): 生成示例图片时使用的提示词(Phrase used when generating example images)
FAQ
Credits
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