T-ponynai3

对于v5版本的一些问题进行一些总结。1，lora兼容性和肢体以及模糊的眼睛问题。lora兼容性是我对于这次训练的最终权重使用的有些过高了，某些情况下会出现过拟合。这个优化版本便是降低了相应权重的版本，肢体的崩坏率以及对于一些lora的兼容应该会好一些，对此我跑了几张使用基于v4.1训练的画风lora的对比图以供参考。眼睛模糊的问题应该是我训练了style_1的原因，使用的原始素材的眼睛就是模糊的，可以通过使用style_3或4来改善。2，体积光的曝光问题。我在测试的时候没有出现过这个问题，导致出现的原因应该是我使用了noise offset的训练参数，使得这个模型对于光的相关提示词的敏感度提升，导致原来一样权重的光的提示词导致的结果会更加明亮，我建议可以尝试不使用括号和数字来提升权重，由于sdxl对于提示词的敏感度，可以试试重复多次一样的提示词，这样不容易导致极端结果。同时，使用这个参数是为了修复少量提示词下的生成结果发黄的问题，对此我跑了几张对比图，以供参考。3，模型的复杂度变低的问题。理论上以及实测来说。v5应该是比之前版本更加干净的和多元的模型，在一些提示词的作用下应该能获得更加精准的表现力，同样的我跑了几张对比图来做比较。这次的训练集并没有采用一些过分复杂的素材，因为我觉得过分复杂的图像会使结果趋于过拟合，这一定导致了不少细节的缺失。目的： 我希望能够得到一个和之前版本有足够大差别的模型，而不是发布一个和之前几乎一摸一样的模型。这次各位的反馈是很好的试错机会，只靠我自己确实没有什么试错成本。在下个版本中我会尝试提高各个不同画风的素材量，使得不同素材的画风能够很好的融合在一起，并且能够实现画风的分离，用特定的prompt来切换画风，这或许需要一些新的训练技巧。感谢各位的反馈！Summarize some issues regarding the v5 version.1, Lora compatibility and issues with limbs and blurred eyes. Lora compatibility is that I used too much final weight for this training, and in some cases, overfitting may occur. This optimized version is the one that reduces the corresponding weight, and the limb collapse rate and compatibility with some Loras should be better. I have run several comparison charts of Loras trained with v4.1 for reference. The problem of blurred eyes should be the reason why I trained style_1. The eyes in the original material used are blurry, and can be improved by using style_3 or 4.2. Exposure issues with volume light. I did not encounter this issue during testing, and the reason for it should be that I used the noise offset training parameter to increase the sensitivity of the model to light related prompt words, resulting in brighter results when the same weight of light prompt words were used. I suggest trying not to use parentheses and numbers to increase the weight. Due to the sensitivity of sdxl to prompt words, you can try repeating the same prompt words multiple times to avoid extreme results. At the same time, using this parameter is to fix the problem of generating yellow results under a small number of prompt words. I have run several comparison graphs for reference.3. The problem of reduced model complexity. In theory and in practice. V5 should be a cleaner and more diverse model than the previous version, and with the help of some prompts, it should be able to achieve more accurate performance. Similarly, I ran several comparison charts for comparison. This training set did not use overly complex materials because I believe that overly complex images tend to overfit the results, which inevitably leads to a certain degree of detail loss.Purpose: I hope to obtain a model that is significantly different from the previous version, rather than releasing a model that is almost identical to the previous version. This feedback from everyone is a great opportunity for trial and error, and I really don't have any trial and error costs on my own. In the next version, I will try to increase the amount of materials for different art styles, so that the art styles of different materials can be well integrated and separated. Using specific prompts to switch art styles may require some new training techniques. Thank you for your feedback!

tPonynai3_v51WeightOptimized.safetensors

v5.1(weight optimized)

v6.5

v6.1

v5.5

v4.1 (Optimized from v4)

v3.5

v3.0

v2.0

v1.0

Files with SHA256: ac17f32d24e526a0503e149667ae52d470723c0ea5716466c149aebe31611606