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https://github.com/openvinotoolkit/stable-diffusion-webui.git
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将无法本地化的内容移到底部
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@ -100,7 +100,6 @@
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"Prompt order": "提示词顺序",
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"Sampler": "采样器",
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"Checkpoint name": "模型(ckpt)名",
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"Hypernetwork": "Hypernetwork",
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"Hypernet str.": "Hypernetwork 强度",
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"Sigma Churn": "Sigma Churn",
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"Sigma min": "最小 Sigma",
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@ -198,7 +197,7 @@
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"Scale to": "指定尺寸缩放",
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"Resize": "缩放",
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"Crop to fit": "裁剪以适应",
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"Upscaler 2 visibility": "放大算法 2 可见度",
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"Upscaler 2 visibility": "放大算法 2 (Upscaler 2) 可见度",
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"GFPGAN visibility": "GFPGAN 可见度",
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"CodeFormer visibility": "CodeFormer 可见度",
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"CodeFormer weight (0 = maximum effect, 1 = minimum effect)": "CodeFormer 权重 (0 = 最大效果, 1 = 最小效果)",
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@ -510,7 +509,6 @@
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"Autocomplete options": "自动补全选项",
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"Enable Autocomplete": "开启Tag补全",
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"Append commas": "附加逗号",
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"Allowed categories for random artists selection when using the Roll button": "使用抽选艺术家按钮时将会随机的艺术家类别",
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"Roll three": "抽三位出来",
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"Generate forever": "无限生成",
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"Cancel generate forever": "停止无限生成",
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@ -519,6 +517,7 @@
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"File with inputs": "含输入内容的文件",
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"Prompts": "提示词",
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"Disabled when launched with --hide-ui-dir-config.": "启动 --hide-ui-dir-config 时禁用",
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"Upscaler": "放大算法",
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"Upscaler 1": "放大算法 1",
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"Upscaler 2": "放大算法 2",
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"Open output directory": "打开输出目录",
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@ -540,5 +539,10 @@
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"Unload VAE and CLIP from VRAM when training": "训练时从显存(VRAM)中取消 VAE 和 CLIP 的加载",
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"Number of pictures displayed on each page": "每页显示的图像数量",
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"Number of grids in each row": "每行显示多少格",
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"how fast should the training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.": "训练应该多快。低值将需要更长的时间来训练,高值可能无法收敛(无法产生准确的结果)以及/也许可能会破坏 embedding(如果你在训练信息文本框中看到 Loss: nan 就会发生这种情况。如果发生这种情况,你需要从较旧的未损坏的备份手动恢复 embedding)\n\n你可以使用以下语法设置单个数值或多个学习率:\n\n 率1:步限1, 率2:步限2, ...\n\n如: 0.005:100, 1e-3:1000, 1e-5\n\n即前 100 步将以 0.005 的速率训练,接着直到 1000 步为止以 1e-3 训练,然后剩余所有步以 1e-5 训练"
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}
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"how fast should the training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.": "训练应该多快。低值将需要更长的时间来训练,高值可能无法收敛(无法产生准确的结果)以及/也许可能会破坏 embedding(如果你在训练信息文本框中看到 Loss: nan 就会发生这种情况。如果发生这种情况,你需要从较旧的未损坏的备份手动恢复 embedding)\n\n你可以使用以下语法设置单个数值或多个学习率:\n\n 率1:步限1, 率2:步限2, ...\n\n如: 0.005:100, 1e-3:1000, 1e-5\n\n即前 100 步将以 0.005 的速率训练,接着直到 1000 步为止以 1e-3 训练,然后剩余所有步以 1e-5 训练",
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"Separate prompts into parts using vertical pipe character (|) and the script will create a picture for every combination of them (except for the first part, which will be present in all combinations)": "用垂直的管道字符 | 将提示语分成若干部分,脚本将为它们的每一个组合创建一幅图片(除了第一部分,所有的组合都会出现)",
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"Select which Real-ESRGAN models to show in the web UI. (Requires restart)": "选择哪些Real-ESRGAN模型显示在用户界面。(需要重新启动)",
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"Face restoration model": "面部修复模型",
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"Allowed categories for random artists selection when using the Roll button": "使用抽选艺术家按钮时将会随机的艺术家类别",
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"Hypernetwork": "超网络(Hypernetwork)"
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}
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