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| license: cc-by-nc-sa-4.0 |
| library_name: diffusers |
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| Thank you for support my work. |
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| <a href="https://www.buymeacoffee.com/bdsqlsz"><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a new graphics card&emoji=😋&slug=bdsqlsz&button_colour=40DCA5&font_colour=ffffff&font_family=Cookie&outline_colour=000000&coffee_colour=FFDD00" /></a> |
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| https://www.buymeacoffee.com/bdsqlsz |
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| Support list will show in main page. |
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| # Support List |
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| ``` |
| DiamondShark |
| Yashamon |
| t4ggno |
| Someone |
| kgmkm_mkgm |
| yacong |
| ``` |
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| Pre-trained models and output samples of ControlNet-LLLite form bdsqlsz |
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| Inference with ComfyUI: https://github.com/kohya-ss/ControlNet-LLLite-ComfyUI |
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| For 1111's Web UI, [sd-webui-controlnet](https://github.com/Mikubill/sd-webui-controlnet) extension supports ControlNet-LLLite. |
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| Training: https://github.com/kohya-ss/sd-scripts/blob/sdxl/docs/train_lllite_README.md |
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| The recommended preprocessing for the animeface model is [Anime-Face-Segmentation](https://github.com/siyeong0/Anime-Face-Segmentation) |
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| # Models |
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| ## Trained on anime model |
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| AnimeFaceSegment、Normal、T2i-Color/Shuffle、lineart_anime_denoise、recolor_luminance |
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| Base Model use[Kohaku-XL](https://civitai.com/models/136389?modelVersionId=150441) |
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| MLSD |
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| Base Model use[ProtoVision XL - High Fidelity 3D](https://civitai.com/models/125703?modelVersionId=144229) |
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| # Japanese Introduction |
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| https://note.com/kagami_kami/n/nf71099b6abe3 |
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| Thank kgmkm_mkgm for introducing these controlllite models and testing. |
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| # Samples |
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| ## AnimeFaceSegmentV2 |
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| ## MLSDV2 |
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| ## Normal_Dsine |
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| ## T2i-Color/Shuffle |
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| ## Lineart_Anime_Denoise |
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| ## Recolor_Luminance |
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| ## Canny |
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| ## DW_OpenPose |
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| ## Tile_Anime |
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| 和其他模型不同，我需要简单解释一下tile模型的用法。 |
| 总的来说，tile模型有三个用法， |
| 1、不输入任何提示词，它可以直接还原参考图的大致效果，然后略微重新修改局部细节，可以用于V2V。(图2) |
| 2、权重设定为0.55~0.75,它可以保持原本构图和姿势的基础上，接受提示词和LoRA的修改。(图3) |
| 3、使用配合放大效果，对每个tiling进行细节增加的同时保持一致性。(图4) |
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| 因为训练时使用的数据集为动漫2D/2.5D模型，所以目前对真实摄影风格的重绘效果并不好，需要等待完成最终版本。 |
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| Unlike other models, I need to briefly explain the usage of the tile model. |
| In general, there are three uses for the tile model, |
| 1. Without entering any prompt words, it can directly restore the approximate effect of the reference image and then slightly modify local details. It can be used for V2V (Figure 2). |
| 2. With a weight setting of 0.55~0.75, it can maintain the original composition and pose while accepting modifications from prompt words and LoRA (Figure 3). |
| 3. Use in conjunction with magnification effects to increase detail for each tiling while maintaining consistency (Figure 4). |
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| Since the dataset used during training is an anime 2D/2.5D model, currently, its repainting effect on real photography styles is not good; we will have to wait until completing its final version. |
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| 目前释放出了α和β两个版本，分别对应1、2以及1、3的用法。 |
| 其中α用于姿势、构图迁移，它的泛化性很强，可以和其他LoRA结合使用。 |
| 而β用于保持一致性和高清放大，它对条件图片更敏感。 |
| 好吧，α是prompt更重要的版本，而β是controlnet更重要的版本。 |
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| Currently, two versions, α and β, have been released, corresponding to the usage of 1、2 and 1、3 respectively. |
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| The α version is used for pose and composition transfer, with strong generalization capabilities that can be combined with other LoRA systems. |
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| On the other hand, the β version is used for maintaining consistency and high-definition magnification; it is more sensitive to conditional images. |
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| In summary, α is a more important version for prompts while β is a more important version for controlnet. |
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| ## Tile_Realistic |
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| Thank for all my supporter. |
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| ``` |
| DiamondShark |
| Yashamon |
| t4ggno |
| Someone |
| kgmkm_mkgm |
| ``` |
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| Even though I broke my foot last week, I still insisted on training the realistic version out. |
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| You can compared with SD1.5 tile below here↓ |
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| For base model using juggernautXL series，so i recommend use their model or merge with it. |
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| Here is comparing with other SDXL model. |
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