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xieyongliangxieyongliang
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cleanup
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‎localizations/zh_CN.json

+109-2
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@@ -633,8 +633,6 @@
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"Username": "用户名",
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"Password": "密码",
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"Email": "电子邮箱",
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"Update": "更新",
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"Delete": "删除",
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"Mismatched username/password or not existed username": "用户名/密码不匹配或用户不存在",
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"Signup failed, please check and retry again": "注册失败，请检查后并重试",
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"Update failed, please check and retry again": "更新失败，请检查后并重试",
@@ -647,6 +645,115 @@
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"Settings saved failed": "设置保存错误",
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"SageMaker endpoint": "SageMaker 端点",
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"User": "用户",
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"Model": "模型",
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"Create new model": "创建新模型",
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"Import Model from Huggingface Hub": "从 HuggingFace Hub 导入模型",
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"Model Path": "模型路径",
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"HuggingFace Token": "HuggingFace Token",
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"Source Checkpoint": "源检查点",
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"Extract EMA Weights": "提取 EMA 权重",
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"Scheduler": "调度器",
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"Lora Model": "Lora模型",
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"Custom Model Name": "自定义模型名称",
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"Lora Weight": "Lora权重",
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"Lora Text Weight": "Lora文本权重",
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"Half Model": "半精度模型",
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"Save Checkpoint to Subdirectory": "保存检查点到子目录",
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"Optimization for training Person": "为训练人物优化",
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"Optimization for training Object/Style": "为训练对象/风格优化",
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"Optimzation for training performance (WIP)": "为训练性能（进行中）优化",
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"Select existing model": "选择已有的模型",
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"Loaded Model:": "加载的模型:",
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"Model Revision:": "模型版本:",
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"V2 Model:": "V2 模型",
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"Has EMA:": "有 EMA",
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"Source Checkpoint:": "源检查点:",
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"Scheduler:": "调度器:",
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"Parameters": "参数",
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"Concepts S3 URI": "Concepts S3 位置",
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"Intervals": "间隔",
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"Training Steps Per Image (Epochs) ": "每张图片的训练步数 (Epochs)",
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"Max Training Steps": "最大训练步数",
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"Pause After N Epochs": "经过若干步后暂停",
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"Amount of time to pause between Epochs, in Seconds": "相邻 Epochs 之间暂停的时间",
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"Use Lifetime Steps/Epochs When Saving": "当保存时使用生命周期步数/ Epoch",
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"Save Preview/Ckpt Every Epoch": "经过若干个 Epoch 保存预览/检查点",
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"Save Checkpoint Frequency": "保存检查点频率",
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"Save Preview(s) Frequency": "保存预览频率",
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"Batch": "批处理",
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"Batch Size": "批量大小",
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"Class Batch Size": "类批量大小",
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"Learning Rate": "学习率",
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"Lora unet Learning Rate ": "Lora unet 学习率",
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"Lora Text Encoder Learning Rate ": "Lora 文本编码器学习率",
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"Scale Learning Rate": "规模学习率",
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"Learning Rate Scheduler": "学习率调度器",
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"Learning Rate Warmup Steps ": "学习率预热步骤",
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"Image Processing": "图像处理",
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"Resolution ": "分辨率",
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"Center Crop": "居中裁剪",
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"Apply Horizontal Flip": "应用水平翻转",
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"Miscellaneous": "杂项",
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"Pretrained VAE Name or Path": "预训练的 VAE 模型名字或路径",
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"Leave blank to use base model VAE.": "留空以使用基础 VAE 模型",
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"Use Concepts List": "使用概念列表",
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"Concepts List": "概念列表",
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"Path to JSON file with concepts to train.": "指向用于训练的概念定义 JSON 文件的路径",
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"Advanced": "高级",
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"Tuning": "调优",
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"Use CPU Only (SLOW)": "仅使用 CPU (慢)",
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"Use LORA": "使用 LORA",
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"Use EMA": "使用 EMA",
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"Use 8bit Adam": "使用8位 Adam",
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"Mixed Precision": "混合精度",
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"Memory Attention": "记忆和注意力",
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"Don't Cache Latents": "不缓存隐向量",
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"Train Text Encoder": "训练文本编码器",
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"Prior Loss Weight": "事先丢弃权重",
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"Pad Tokens": "填补 Token",
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"Shuffle Tags": "随机标签",
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"Max Token Length": "最大 Token 长度",
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"Train Imagic Only": "仅训练 Imagic",
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"Gradients": "梯度",
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"Gradient Checkpointing": "梯度检查点",
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"Gradient Accumulation Steps": "梯度累计步数",
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"Adam Advanced": "Adam 高级选项",
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"Adam Beta 1": "Adam Beta 1 ",
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"Adam Beta 2": "Adam Beta 2",
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"Adam Weight Decay": "Adam 权重衰减",
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"Adam Epsilon": "Adam Epsilon",
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"Concepts": "概念",
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"Concept 1": "概念1",
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"Concept 2": "概念2",
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"Concept 3": "概念3",
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"Maximum Training Steps": "最大训练步数",
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"Directories": "目录",
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"Dataset Directory": "数据集目录",
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"Classification Dataset Directory": "分类数据集目录",
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"(Optional) Path to directory with classification/regularization images": "(可选) 指向带有分类和正则化图像目录的路径",
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"Filewords": "Filewords",
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"Instance Token": "实例 Token",
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"When using [filewords], this is the subject to use when building prompts.": "当使用 [filewords]，这是主题用于构建提示词",
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"Class Token": "分类 Token",
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"When using [filewords], this is the class to use when building prompts.": "当使用 [filewords]，这是分类用于构建提示词",
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"Instance Prompt": "实例提示词",
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"Optionally use [filewords] to read image captions from files.": "可选使用[filewords]从文件中读取图像标题",
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"Class Prompt": "分类提示词",
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"Classification Image Negative Prompt": "分类图像负向提示词",
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"Sample Image Prompt": "验本图像提示词",
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"Leave blank to use instance prompt. Optionally use [filewords] to base sample captions on instance images.": "留空以使用实例提示词。可选使用[filewords]在实例图像上基础采样标题",
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"Sample Prompt Template File": "采样提示词模版文件",
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"Enter the path to a txt file containing sample prompts.": "输入指向包含采样提示词的文本文件的路径",
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"Sample Image Negative Prompt": "采样图像负向提示词",
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"Image Generation": "图像生成",
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"Total Number of Class/Reg Images": "Class/Reg 图像总数",
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"Classification CFG Scale ": "分类扩散度",
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"Classification Steps ": "分类步数",
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"Number of Samples to Generate": "生成的采样数",
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"Sample Seed": "采样种子",
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"Sample CFG Scale ": "采样扩散度",
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"Sample Steps": "采样步数",
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"Cancel": "取消",
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"--------": "--------"
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}

‎localizations/zh_TW.json

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@@ -636,6 +636,115 @@
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"Settings saved failed": "設置保存錯誤",
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"SageMaker endpoint": "SageMaker 端點",
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"User": "使用者",
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"Model": "模型",
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"Create new model": "創建新模型",
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"Import Model from Huggingface Hub": "從 HuggingFace Hub 導入模型",
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"Model Path": "模型路徑",
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"HuggingFace Token": "HuggingFace Token",
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"Source Checkpoint": "源檢查點",
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"Extract EMA Weights": "提取 EMA 權重",
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"Scheduler": "調度器",
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"Lora Model": "Lora模型",
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"Custom Model Name": "自定義模型名稱",
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"Lora Weight": "Lora權重",
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"Lora Text Weight": "Lora文本權重",
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"Half Model": "半精度模型",
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"Save Checkpoint to Subdirectory": "保存檢查點到子目錄",
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"Optimization for training Person": "為訓練人物優化",
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"Optimization for training Object/Style": "為訓練對象/風格優化",
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"Optimzation for training performance (WIP)": "為訓練性能（進行中）優化",
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"Select existing model": "選擇已有的模型",
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"Loaded Model:": "加載的模型:",
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"Model Revision:": "模型版本:",
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"V2 Model:": "V2 模型",
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"Has EMA:": "有 EMA",
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"Source Checkpoint:": "源檢查點:",
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"Scheduler:": "調度器:",
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"Parameters": "參數",
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"Concepts S3 URI": "Concepts S3 位置",
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"Intervals": "間隔",
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"Training Steps Per Image (Epochs) ": "每張圖片的訓練步數 (Epochs)",
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"Max Training Steps": "最大訓練步數",
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"Pause After N Epochs": "經過若干步後暫停",
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"Amount of time to pause between Epochs, in Seconds": "相鄰 Epochs 之間暫停的時間",
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"Use Lifetime Steps/Epochs When Saving": "當保存時使用生命週期步數/ Epoch",
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"Save Preview/Ckpt Every Epoch": "經過若干個 Epoch 保存預覽/檢查點",
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"Save Checkpoint Frequency": "保存檢查點頻率",
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"Save Preview(s) Frequency": "保存預覽頻率",
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"Batch": "批處理",
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"Batch Size": "批量大小",
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"Class Batch Size": "類批量大小",
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"Learning Rate": "學習率",
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"Lora unet Learning Rate ": "Lora unet 學習率",
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"Lora Text Encoder Learning Rate ": "Lora 文本編碼器學習率",
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"Scale Learning Rate": "規模學習率",
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"Learning Rate Scheduler": "學習率調度器",
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"Learning Rate Warmup Steps ": "學習率預熱步驟",
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"Image Processing": "圖像處理",
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"Resolution ": "分辨率",
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"Center Crop": "居中裁剪",
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"Apply Horizontal Flip": "應用水平翻轉",
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"Miscellaneous": "雜項",
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"Pretrained VAE Name or Path": "預訓練的 VAE 模型名字或路徑",
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"Leave blank to use base model VAE.": "留空以使用基礎 VAE 模型",
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"Use Concepts List": "使用概念列表",
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"Concepts List": "概念列表",
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"Path to JSON file with concepts to train.": "指向用於訓練的概念定義 JSON 文件的路徑",
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"Advanced": "高級",
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"Tuning": "調優",
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"Use CPU Only (SLOW)": "僅使用 CPU (慢)",
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"Use LORA": "使用 LORA",
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"Use EMA": "使用 EMA",
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"Use 8bit Adam": "使用8位 Adam",
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"Mixed Precision": "混合精度",
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"Memory Attention": "記憶和注意力",
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"Don't Cache Latents": "不緩存隱向量",
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"Train Text Encoder": "訓練文本編碼器",
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"Prior Loss Weight": "事先丟棄權重",
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"Pad Tokens": "填補 Token",
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"Shuffle Tags": "隨機標籤",
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"Max Token Length": "最大 Token 長度",
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"Train Imagic Only": "僅訓練 Imagic",
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"Gradients": "梯度",
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"Gradient Checkpointing": "梯度檢查點",
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"Gradient Accumulation Steps": "梯度累計步數",
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"Adam Advanced": "Adam 高級選項",
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"Adam Beta 1": "Adam Beta 1 ",
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"Adam Beta 2": "Adam Beta 2",
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"Adam Weight Decay": "Adam 權重衰減",
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"Adam Epsilon": "Adam Epsilon",
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"Concepts": "概念",
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"Concept 1": "概念1",
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"Concept 2": "概念2",
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"Concept 3": "概念3",
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"Maximum Training Steps": "最大訓練步數",
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"Directories": "目錄",
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"Dataset Directory": "數據集目錄",
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"Classification Dataset Directory": "分類數據集目錄",
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"(Optional) Path to directory with classification/regularization images": "(可選) 指向帶有分類和正則化圖像目錄的路徑",
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"Filewords": "Filewords",
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"Instance Token": "實例 Token",
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"When using [filewords], this is the subject to use when building prompts.": "當使用 [filewords]，這是主題用於構建提示詞",
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"Class Token": "分類 Token",
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"When using [filewords], this is the class to use when building prompts.": "當使用 [filewords]，這是分類用於構建提示詞",
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"Instance Prompt": "實例提示詞",
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"Optionally use [filewords] to read image captions from files.": "可選使用[filewords]從文件中讀取圖像標題",
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"Class Prompt": "分類提示詞",
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"Classification Image Negative Prompt": "分類圖像負向提示詞",
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"Sample Image Prompt": "驗本圖像提示詞",
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"Leave blank to use instance prompt. Optionally use [filewords] to base sample captions on instance images.": "留空以使用實例提示詞。可選使用[filewords]在實例圖像上基礎採樣標題",
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"Sample Prompt Template File": "採樣提示詞模版文件",
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"Enter the path to a txt file containing sample prompts.": "輸入指向包含採樣提示詞的文本文件的路徑",
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"Sample Image Negative Prompt": "採樣圖像負向提示詞",
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"Image Generation": "圖像生成",
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"Total Number of Class/Reg Images": "Class/Reg 圖像總數",
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"Classification CFG Scale ": "分類擴散度",
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"Classification Steps ": "分類步數",
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"Number of Samples to Generate": "生成的採樣數",
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"Sample Seed": "採樣種子",
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"Sample CFG Scale ": "採樣擴散度",
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"Sample Steps": "採樣步數",
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"Cancel": "取消",
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"--------": "--------"
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}

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