此嵌入專注於修正手指數量與形狀問題，可能導致模型風格改變
v5:
negative_hand-neg訓練於10張圖像而成。
v22
使用75個vector，訓練資料使用v5與其他負面嵌入產生的兩百張圖像。
v49
使用32個vector，訓練資料使用不同風格模型與其他負面嵌入產生的六百張圖像。
Translated by ChatGPT
This embedding focuses on correcting issues related to the number and shape of fingers, which may result in a change in the model's style.
v5:
negative_hand-neg is trained on 10 images.
v22:
Utilizing 75 vectors, the training data consists of 200 images generated from v5 and other negative embeddings.
v49
Utilizing 32 vectors, the training data consists of 600 images generated from different style models and other negative embeddings.
The training data is generated from the old version and other negative embeddings, totaling 600 images with dimensions of 512*512.
32 vectors per token.
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