用感觉来理解未知的事物，这疑似有点太原始了，但是你有更好的方法吗。Understanding the unknown through sensation, this method may be somewhat primitive, but do you have a better approach.<hr />一次完整的模型处理需要13个流程，这些流程分为3种，总之我会尽量完整的解释给你们A complete model processing requires 13 processes, which are divided into 3 types. In short, I will try my best to explain it to you thoroughly流程1拆解模型 A ：(被提取模型) 模型 B ：Extract component B 模型 C : Extract component Cα= -1Process 1 BreakdownModel a：( extracted model ) Model b ：Extract component B Model c : Extract component Cα= -1流程2阶段提取模型 A ：流程1提取物 1 模型 B ：(被提取模型) 模型 模型 C ：流程1提取物 1α= 2进行这一步混合后会得到 流程1提取物2，之后你需要不断更换模型A和模型C 用于得到 流程1提取物4Phase 2 extractionModel A: Process 1 Extract 1 Model B: (Extracted Model) Model C: Process 1 Extract 1α = 2After this step of mixing, you will obtain Process 1 Extract 2. Then, you need to continuously switch between Model A and Model C to obtain Process 1 Extract 4我简单介绍一下获取的模型类型Let me briefly introduce the types of models obtained流程1提取物 1：通过提取模型以及混合算法，去除了被提取模型的基础部分，而留下来的则是这个模型的画风。这部分我称作画风1.0Process 1 Extract 1：By extracting the model and using a mixed algorithm, the foundational parts of the extracted model have been removed, leaving behind what I refer to as the style of the model. This part I call Style 1.0流程1提取物 2：基础1.0 、流程1提取物 3：画风2.0 、流程1提取物 4：基础2.0Process 1 Extract 2：Basic 1.0 Process 1 Extract 3：Style 2.0 Process 1 Extract 4：Basic 2.0流程3提纯 流程3需要结合之前的流程使用模型 A ：画风2.0 模型 B ：画风2.0拆解 流程1提取物 3 模型 C ：画风2.0α = -1现在这个模型就回到了未拆解的阶段，并成功的进行了活性化基础2.0的混合路线也是如此Phase 3 refine Process 3 needs to be used in conjunction with the previous processesModel A ：Style 2.0 模型 B ：Style 2.0 Breakdown Process 1 Extract 3 模型 C ：Style 2.0α = -1The model has now returned to the unassembled stage and has successfully been ActivationThe mixed route of Basic 2.0 is the same.这种方式也可以增加提取物信息的深度，不过需要进行一些调整This method can also enhance the depth of the extract information, but some adjustments are needed我承认我并不是一个专业的研究者，我所做的一切或许毫无意义，又或者我发现的都是错误的，总之，我现在已经感到了疲劳，显然我已经失去了热情。我把大量的时间用在模型混合上，但始终没有得到突破式的发展，或许从最开始我的方向便是错误的。模型训练是AI的正确路线，模型混合不是。模型版本升级是正确路线，模型混合不是。所以你有什么想法吗。

KM_Model_splicing_material_demonstration

Model link :<a target="_blank" rel="ugc" href="https://civitai.com/models/16390?modelVersionId=31218">https://civitai.com/models/16390?modelVersionId=31218</a> <a target="_blank" rel="ugc" href="https://civitai.com/models/112214/anime3d-mix">https://civitai.com/models/112214/anime3d-mix</a>画风模型是通过调整数值获得的，基础模型是按照设想中的流程进行提取的。我在混合时发现重复某一流程的提取方式，提取物会逐渐稳定在同一阶段。The style model is obtained by adjusting numerical values, while the basic model is extracted according to the envisioned process. I found that when mixing, the extraction method of repeating a certain process causes the extract to gradually stabilize at the same stage { "format": "pt", "sd_merge_recipe": { "type": "sd-webui-supermerger", "weights_alpha": null, "weights_beta": null, "weights_alpha_orig": null, "weights_beta_orig": null, "model_a": "cf8a2eb7ab8631d5a1b66a8d42b6cb667bb8ad6a7d413a386d929031939f0b89", "model_b": "3261979b95a53b65cad3f0b10c717d444a76fd9815c36dc5964d97b5a9eac8ee", "model_c": "cf8a2eb7ab8631d5a1b66a8d42b6cb667bb8ad6a7d413a386d929031939f0b89", "base_alpha": 0.576, "base_beta": 0.611, "mode": "Add difference", "mbw": false, "elemental_merge": "", "calcmode": "trainDifference", "Off": [ "" ] }, "sd_merge_models": { "cf8a2eb7ab8631d5a1b66a8d42b6cb667bb8ad6a7d413a386d929031939f0b89": { "name": "待拆解_新素材_画风元素_(anime3d)3d", "legacy_hash": "13910461" }, "3261979b95a53b65cad3f0b10c717d444a76fd9815c36dc5964d97b5a9eac8ee": { "name": "3素材_模型拆分_基础_8-10 模型拆解orientalMix 2.1.fp16", "legacy_hash": "67a5ef4f" } } }目前仍在测试规范化提取流程的可行性，但我认为这可能太早了。而且规范化的东西没有任何特点。或许调整数值才是融合模型的乐趣所在？Currently, the feasibility of the standardized extraction process is still being tested, but I believe it may be too early. Moreover, standardized elements lack any distinctive features. Perhaps adjusting the values is where the enjoyment of the integrated model lies

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