A Different Approach

It’s been quite some time since the previous update, and this version takes a noticeably different direction. While it may not be revolutionary compared to other models on this site (after all, it’s still a merge), the goal here was to focus on several key aspects:

High realism without relying on LoRAs or embeddings.

A strong base model provides much more flexibility if you decide to experiment with additional tools later.

Works well with a minimal negative prompt.

In many cases, shorter negative prompts actually produce more natural results. Of course, you can still expand it with longer prompts or embeddings whenever needed.

Stable results for poses, hands, and other details.

Even within these limitations, the model aims to maintain consistent anatomy and structure.

Control over lighting and shadows directly through prompts.

Although there are excellent LoRAs for lighting and noise adjustments, the model already offers solid control by default.

Handles even the wildest wildcard prompts.

You can throw in random lists of locations, time periods, clothing styles, materials, or abstract concepts—especially those generated or enhanced by your local GPT.

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一种不同的方向

距离上一次更新已经过去了一段时间，而这次的版本与之前相比有着明显的变化。虽然它未必算是这个网站上最具突破性的模型（毕竟本质上仍然是一个合并模型），但这次的重点主要放在几个非常具体的方向上：

在不使用 LoRA 或 Embedding 的情况下实现高真实度。

一个强大的基础模型可以为后续的创作提供更大的灵活空间，如果需要，你依然可以在之后自由添加这些工具。

即使使用很简短的负面提示（negative prompt）也能正常工作。

很多时候，更简单的负面提示反而能带来更自然的结果。当然，你仍然可以根据需要加入更长的提示或 embedding。

在姿势、手部以及其他细节方面保持稳定一致。

在这些限制条件下，模型仍然尽量保证人物结构与姿态的稳定性。

仅通过提示词即可控制光线与明暗。

虽然市面上有许多优秀的 LoRA 用于光线或噪声调整，但这个模型本身已经具备不错的默认控制能力。

能够很好地响应各种“疯狂”的 wildcard 列表。

无论是随机生成的地点、时代背景、服装材质，还是各种概念设定，都可以通过你的本地 GPT 生成并扩展，然后直接用于提示词中。