一、训练DreamBooth时,相关代码的细节小计 ** class_labels = timesteps 时,模型的前向传播怎么走?待深入去看 ** 利用class_prompt去生成数据,而不是instance_prompt class DreamBoothDataset(Dataset):"""A dataset to prepare the instance and
using dapers on diffusers: Dreambooth, Texual Inversion, LoRA and IP-Adapter 参考自:https://huggingface.co/docs/diffusers/using-diffusers/loading_adapters 如今,对于 diffusion 模型,有许多高效的训练技术来微调一个定制化的模型,能够
Textual Inversion on diffusers 参考自官方文档:https://huggingface.co/docs/diffusers/training/textual_inversion_inference、https://huggingface.co/docs/diffusers/training/text_inversion?installation=PyTorch