"Train an embedding; must specify a directory with a set of 1:1 ratio images":"訓練 embedding； 必須指定一組具有 1:1 比例圖像的目錄",
"Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images":"訓練 embedding 或者 hypernetwork； 必須指定一組具有 1:1 比例圖像的目錄",
"Apply color correction to img2img results to match original colors.":"對圖生圖結果套用顏色校正以匹配原始顏色",
"Save a copy of image before applying color correction to img2img results":"在對圖生圖結果套用顏色校正之前儲存圖像副本",
"With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising).":"在進行圖生圖的時候，確切地執行滑塊指定的疊代步數（正常情況下更弱的去噪需要更少的疊代步數）",
"Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply.":"在 K 採樣器中啟用量化以獲得更清晰，更清晰的結果。這可能會改變現有的隨機種子。需要重新啟動才能套用",
"Make K-diffusion samplers produce same images in a batch as when making a single image":"使 K-diffusion 採樣器批量生成與生成單個圖像時產出相同的圖像",
"Increase coherency by padding from the last comma within n tokens when using more than 75 tokens":"當使用超過 75 個 token 時，通過從 n 個 token 中的最後一個逗號填補來提高一致性",
"Filter NSFW content":"過濾成人內容",
"Stop At last layers of CLIP model":"在 CLIP 模型的最後哪一層停下",
"Interrogate: keep models in VRAM":"反推： 將模型儲存在顯存（VRAM）中",
"Interrogate: use artists from artists.csv":"反推： 使用 artists.csv 中的藝術家",
"Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators).":"反推： 在生成結果中包含與模型標籤相匹配的等級（對基於生成自然語言描述的反推沒有影響）",
"Interrogate: num_beams for BLIP":"反推： BLIP 的 num_beams",
"Add model hash to generation information":"將模型的雜湊值加入到生成資訊",
"Add model name to generation information":"將模型名稱加入到生成資訊",
"When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint.":"當從文本讀取生成參數到 UI（從 PNG 資訊或粘貼文本）時，不要更改選定的模型權重存檔點",
"Which algorithm to use to produce the image":"使用哪種演算法生成圖像",
"Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps to higher than 30-40 does not help":"Euler Ancestral - 非常有創意，可以根據疊代步數獲得完全不同的圖像，將疊代步數設定為高於 30-40 不會有正面作用",
"Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition":"使用兩步處理的時候以較小的解析度生成初步圖像，接著放大圖像，然後在不更改構圖的情況下改進其中的細節",
"Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.":"決定演算法對圖像內容的影響程度。設定 0 時，什麼都不會改變，而在 1 時，你將獲得不相關的圖像。值低於 1.0 時，處理的疊代步數將少於「採樣疊代步數」滑塊指定的步數",
"How many batches of images to create":"建立多少批次的圖像",
"How many image to create in a single batch":"每批建立多少圖像",
"Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results":"Classifier Free Guidance Scale - 圖像應在多大程度上服從提示詞 - 較低的值會產生更有創意的結果",
"A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result":"一個固定隨機數生成器輸出的值 — 以相同參數和隨機種子生成的圖像會得到相同的結果",
"Set seed to -1, which will cause a new random number to be used every time":"將隨機種子設定為-1，則每次都會使用一個新的隨機數",
"Reuse seed from last generation, mostly useful if it was randomed":"重用上一次使用的隨機種子，如果想要固定結果就會很有用",
"Seed of a different picture to be mixed into the generation.":"將要參與生成的另一張圖的隨機種子",
"How strong of a variation to produce. At 0, there will be no effect. At 1, you will get the complete picture with variation seed (except for ancestral samplers, where you will just get something).":"想要產生多強烈的變化。設為 0 時，將沒有效果。設為 1 時，你將獲得完全產自差異隨機種子的圖像（ancestral 採樣器除外，你只是單純地生成了一些東西）",
"Make an attempt to produce a picture similar to what would have been produced with same seed at specified resolution":"嘗試生成與在指定解析度下使用相同隨機種子生成的圖像相似的圖片",
"This text is used to rotate the feature space of the imgs embs":"此文本用於旋轉圖集 embeddings 的特徵空間",
"Separate values for X axis using commas.":"使用逗號分隔 X 軸的值",
"Separate values for Y axis using commas.":"使用逗號分隔 Y 軸的值",
"In loopback mode, on each loop the denoising strength is multiplied by this value. <1 means decreasing variety so your sequence will converge on a fixed picture. >1 means increasing variety so your sequence will become more and more chaotic.":"在回送模式下，在每個循環中，去噪強度都會乘以該值。<1 表示減少多樣性，因此你的這一組圖將集中在固定的圖像上。>1 意味著增加多樣性，因此你的這一組圖將變得越來越混亂",
"For SD upscale, how much overlap in pixels should there be between tiles. Tiles overlap so that when they are merged back into one picture, there is no clearly visible seam.":"使用 SD 放大時，圖塊之間應該有多少畫素重疊。圖塊之間需要重疊才可以讓它們在合併回一張圖像時，沒有清晰可見的接縫",
"A directory on the same machine where the server is running.":"與伺服器主機上的目錄",
"1st and last digit must be 1. ex:'1, 2, 1'":"第一個和最後一個數字必須是 1。例：'1, 2, 1'",
"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.":"訓練應該多快。低值將需要更長的時間來訓練，高值可能無法收斂（無法產生準確的結果）以及／也許可能會破壞 embedding（如果你在訓練資訊文字方塊中看到 Loss: nan 就會發生這種情況。如果發生這種情況，你需要從較舊的未損壞的備份手動恢復 embedding）\n\n你可以使用以下語法設定單個數值或多個學習率：\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 步將以 0.005 的速率訓練，接著直到 1000 步為止以 1e-3 訓練，然後剩餘所有步以 1e-5 訓練",
"Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]; leave empty for default.":"使用以下標籤定義如何選擇圖像的檔案名： [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]； 預設請留空",
"If this option is enabled, watermark will not be added to created images. Warning: if you do not add watermark, you may be behaving in an unethical manner.":"如果啟用此選項，浮水印將不會加入到生成出來的圖像中。警告：如果你不加入浮水印，你的行為可能是不符合道德操守的",
"Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]; leave empty for default.":"使用以下標籤定義如何選擇圖像和概覽圖的子目錄： [steps], [cfg], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [prompt_words], [date], [datetime], [job_timestamp]； 預設請留空",
"Restore low quality faces using GFPGAN neural network":"使用 GFPGAN 神經網路修復低品質面部",
"This regular expression will be used extract words from filename, and they will be joined using the option below into label text used for training. Leave empty to keep filename text as it is.":"此正則表達式將用於從檔案名中提取單詞，並將使用以下選項將它們接合到用於訓練的標籤文本中。留空以保持檔案名文本不變",
"This string will be used to join split words into a single line if the option above is enabled.":"如果啟用了上述選項，則此處的字元會用於將拆分的單詞接合為同一行",
"List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.":"設定名稱列表，以逗號分隔，設定應轉到頂部的快速存取列，而不是通常的設定頁籤。有關設定名稱，請參見 modules/shared.py。需要重新啟動才能套用",
"If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.":"如果這個值不為零，它將被加入到隨機種子中，並在使用帶有 Eta 的採樣器時用於初始化隨機噪聲。你可以使用它來產生更多的圖像變化，或者你可以使用它來模仿其他軟體生成的圖像，如果你知道你在做什麼",
