Speculation (Model elements)版本Element splicing 6-28-20 (ID: 604398)

我不知道你们怎么看待模型混合，但是LORA明显比模型混合更有热度,我会尽力去尝试给你们演示我的发现，当然你们也可以解释这些现象,

I don't know how you view model blending, but Lora is clearly more popular than model blending. I will do my best to demonstrate my findings to you, and of course, you can also explain these phenomena.

模型的属性：不是指画面属性，我发现了两个特殊的模型，因为它们的特点非常明显所以我称呼这些模型为基础模型，和画风模型,

Model attributes: It does not refer to visual attributes. I have discovered two special models. Because their characteristics are very obvious, I refer to these models as basic models and art style models.

基础模型：你应该能看出来这两个的相似点，那就是缺少特色,事实上这种模型也存在超浓缩无法正常生成图像的现象,

Basic model: You should be able to see the similarity between the two, which is the lack of distinctive features. In fact, this type of model also has the phenomenon of super-condensation that cannot generate images normally.

画风模型：这类模型缺少画面生成的完整性，如果再次减弱模型的基础元素的话就会彻底无法正常的生成图像,我猜测这是对模型元素的提纯

Art Style Model: This type of model lacks the completeness of image generation. If the basic elements of the model are further weakened, it will completely fail to generate images normally. I speculate that this is a refinement of the model elements.

嗯，我想也不会有人在意这些，糟糕的是我也非常怀疑我的发现是否正确，我感觉自己就是舞台上小丑,糟糕透了

Well, I don't think anyone cares about these things. The problem is that I also highly doubt whether my discovery is correct. I feel like I'm just a clown on stage. It's really terrible.

描述:

我先向你们展示简单的模型拼接，之后在上传使用的素材，因为纯粹的模型元素并不是那么好看

I will first show you the simple model splicing, and then upload the materials used, because pure model elements are not so good-looking.

只要加上质量提示词所有的模型都将是美丽的

As long as quality prompts are added, all models will be beautiful.

{ "sd_merge_models": { "d9e235f231d3a76713c6c02a833b73a15e36dd1190600f48cfd7de5046af4cfb": { "name": "1混合_2中适应性_画风元素_低完成度+特征模型+铅笔特征写实1", "legacy_hash": "496f1b93" }, "f9f3ce99360355433e1da67b8684aa0c175531d60d63afba59464d1b6d0dd447": { "name": "新素材_基础元素_画风融合测试6-23-42.fp16", "legacy_hash": "d4e89f22" } }, "sd_merge_recipe": { "type": "sd-webui-supermerger", "weights_alpha": null, "weights_beta": null, "weights_alpha_orig": null, "weights_beta_orig": null, "model_a": "d9e235f231d3a76713c6c02a833b73a15e36dd1190600f48cfd7de5046af4cfb", "model_b": "f9f3ce99360355433e1da67b8684aa0c175531d60d63afba59464d1b6d0dd447", "model_c": "d9e235f231d3a76713c6c02a833b73a15e36dd1190600f48cfd7de5046af4cfb", "base_alpha": 0.7, "base_beta": 0.02, "mode": "Add difference", "mbw": false, "elemental_merge": "", "calcmode": "trainDifference", "Off": [ "" ] }, "format": "pt" }

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