这是我基于1.5的底模训练出来的一个关于中国风,潮汕风格的lora,训练素材有个70 80张,可能素材有部分是别墅的素材,所以有时候出的图会层高会显得比较高,至于参数都是参考同类型的lora模型进行微调的,大差不差,发出来希望有人使用然后进行点评. 我自己试了试maijicmix为底模的效果真不错,然后权重控制在0.6 0.7 0.8效果都不差,我po个图出来给你们看下 Here's the translation of your message into English:"I have trained a LoRA (Language-Optimized ReAding) model based on a GPT-1.5 underlying model, focusing on Chinese and Chaoshan-style aesthetics. The training dataset consists of around 70 to 80 images. Some of the materials may include villa-style elements, which can sometimes result in taller structures in the generated images.As for the model parameters, I fine-tuned them based on similar LoRA models, achieving fairly good results. I've tried using 'maijicmix' as the base model, and the performance has been impressive. Adjusting the weights within the range of 0.6 to 0.8 has also yielded satisfactory results.I'm sharing a sample image that I generated for you to take a look at. I hope someone finds it useful and can provide feedback.If you have any questions or need further information, feel free to ask. Thank you for your interest!"

中式室内装修_China_style_renovation

这是我基于1.5的底模训练出来的一个关于中国风,潮汕风格的lora,训练素材有个70 80张,可能素材有部分是别墅的素材,所以有时候出的图会层高会显得比较高,至于参数都是参考同类型的lora模型进行微调的,大差不差,发出来希望有人使用然后进行点评. 我自己试了试maijicmix为底模的效果真不错,然后权重控制在0.6 0.7 0.8效果都不差,我po个图出来给你们看下 I have trained a LoRA (Language-Optimized ReAding) model based on a GPT-1.5 underlying model, focusing on Chinese and Chaoshan-style aesthetics. The training dataset consists of around 70 to 80 images. Some of the materials may include villa-style elements, which can sometimes result in taller structures in the generated images.As for the model parameters, I fine-tuned them based on similar LoRA models, achieving fairly good results. I've tried using 'chilloutmix' as the base model, and the performance has been impressive. Adjusting the weights within the range of 0.6 to 0.8 has also yielded satisfactory results.I'm sharing a sample image that I generated for you to take a look at. I hope someone finds it useful and can provide feedback.If you have any questions or need further information, feel free to ask. Thank you for your interest!

Files with SHA256: b04c562bc7ca0e0531b71f6e8afd4bf1966648eedb6b06c5c4530e84845487bd