生成与训练集同长宽比例的图 > 正方形训练接的图生成长方形比例的图 > 比例差距较大的图(如2:3训练集的lora画3:2的full body图片) (10). 在没有明显关系的数据集内切不可把人物切碎, 不然会出鬼图.(后面素材剪切介绍会详细说) 2. 如何判定素材质量 (1). 细节是否清晰, 有没有出现细节反转(比如瞳色...
一般需要删掉的标签:如人物特征 long hair,blue eyes 这类。不需要删掉的标签:如人物动作 stand,run 这类,人物表情 smile,open mouth 这类,背景 simple background,white background 这类,画幅位置等 full body,upper body,close up 这类。 添加触发词(可选)整理每个图片的标签,每个图片对应的标签第一句加上你...
https://github.com/bmaltais/kohya_ss/wiki/LoRA-training-parameters 附一份C站上某个lora模型文件的训练参数供一览: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 ...
Full fp16 training (experimental) 复选框:如果打开之前的选项 Mixed precision “混合精度”(fp16或bf16),则在训练期间将使用 32 位和 16 位数据的混合。但如果打开此选项,则所有权重数据将是 16-位(fp16 格式),即不会混合32 位数据。 这样虽然节省了VRAM,但某些数据的准确率则减半,因此学习准确率...
https://github.com/bmaltais/kohya_ss/wiki/LoRA-training-parameters 还是不懂,也可以问各种gpt或者直接翻译成中文阅读即可。 现在主流最广泛使用的模型存储格式为 huggingface的safetensors https://github.com/huggingface/safetensors kohya_ss里默认会把训练参数填到safetensors的metadata里。
This option enables the full bfloat16 training (includes gradients). This option is useful to reduce the GPU memory usage. However, bitsandbytes==0.35 doesn't seem to support this. Please use a newer version of bitsandbytes or another optimizer. ...
When training on faces, it is recommended that no other faces appear in the training set as we don't want to create an ambiguous notion of what is the face we're training on. Close-up photosare important to achieve realism, however good full-body shots should also be...
Because I just so happen to have all my pro gear with me since I was shooting the story of the yoga teacher training program. I was a wedding photographer, who happen to meet a couple that just got married, who had their wedding clothes with them. AND WE WERE ALL IN THE FRENCH ALPS...
Depending on the training of the model, the character might be fitted to an outfit, a specific hairstyle, or even a certain facial expression. However, some character LoRA makes it possible to put your chosen character into new outfits and settings, giving them an added level of charm. ...
Once this is all done, we can begin training. Training the LoRA model Resume_Training=False# If you're not satisfied with the result, Set to True, run again the cell and it will continue training the current model.Training_Epochs=50# Epoch = Number of steps/images.Learning_Rate="3e-6...