它是在 FLUX.DEV完整模型上使用FP16的精度训练的，同时将clip-L模型换成了CLIP-GmP-ViT-L-14 模型，然后使用了joy_caption_two进行自然语言训练集打标。这意味着你如果加载flux.dev完整模型全精度和T5-clip以及CLIP-GmP-ViT-L-14全精度进行生图时，可能需要35G显存。

我同样没有设置触发词，你只需要直接了当的输入你想要的画面即可。或者你可以将我的示例图拖入comfyui，以查看我的提示词写法。

需要注意的是：我的训练集中并没有包含任何NSFW画面，如果你需要绘制例如我的图集中图一和图二的裸体画面，你可能需要加载别的微调模型或者lora。

训练集中包含的概念装束有：比基尼，皮裤，厚底高跟鞋，短裙，抹胸，人种以欧美为主，包含多人。

It is trained on the FLUX.DEV full model with FP16 precision, and the clip-L model is replaced with the CLIP-GmP-ViT-L-14 model, and then joy_caption_two is used for natural language training set labeling. This means that if you load the flux.dev full model with full precision and T5-clip and CLIP-GmP-ViT-L-14 with full precision for raw images, you may need 35G video memory.

I also did not set trigger words, you just need to directly enter the picture you want. Or you can drag my example picture into comfyui to see how I write my prompt words.

It should be noted that my training set does not contain any NSFW pictures. If you need to draw nude pictures such as Figure 1 and Figure 2 in my collection, you may need to load other fine-tuning models or lora.

The concept costumes included in the training set are: bikini, leather pants, thick-soled high heels, short skirts, tube tops, and the races are mainly European and American, including multiple people.