Learn to train SDXL with LORA for custom AI image styles. Master dataset preparation, training parameters, and model selection to create unique visual styles using Stable Diffusion.
现在想想,我炼丹能炼到V19那种程度,光是读那篇“THE OTHER LoRA TRAINING RENTRY”就读了有十遍吧…… (擦,明明是小结,结果又说了一千字) (实际上根本没小结,就是想到哪儿白话到哪儿) 最最后附上一些我做的沙雕AI主题梗图: 如果你读到了这里,谢谢你的耐心!!!
size mismatch for mid_block.attentions.0.proj_out.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]). 00:50:24-776948 ERROR Training failed / 训练失败 训练的配置,model_train_type = "sd-lora" p...
launch --num_cpu_threads_per_process=2 "./sdxl_train_network.py" --enable_bucket --min_bucket_reso=256 --max_bucket_reso=2048 --pretrained_model_name_or_path="C:/ai/models/Stable-diffusion/sd_xl_base_1.0.safetensors" --train_data_dir="C:/ai/lora/Training/img" --reg_data_dir=...
Adds MPS bugfixes to the SDXL example training scripts. I haven't really completed this yet, I'm looking for comments on the approach, or whether it should be done at all. On an M3 Max, I get reasonable speeds for training. ️ 3 apple mps: training support for SDXL LoRA bfc...
cell3:进行lora训练: !accelerate launch /workspace/diffusers/examples/dreambooth/train_dreambooth_lora_sdxl.py \ --pretrained_model_name_or_path=stabilityai \ --instance_data_dir=/project/data/toy-jensen \ --output_dir=/project/models/tuned-toy-jensen \ ...
steps: 50%|████████████████████████▌ | 6360/12720 [1:16:04<1:16:04, 1.39it/s, avr_loss=0.0625]saving checkpoint: ./output\AN6-000006.safetensorsepoch 7/12steps: 58%|████████████████████████████▌ | 7420/12720 [1...
if args.seed is not None: set_seed(args.seed) # We only train the additional adapter LoRA layers vae.eval() text_encoder_one.eval() text_encoder_two.eval() unet.eval() def compute_snr(timesteps): """ Computes SNR as per https://kgithub.com/TiankaiHang/Min-SNR-Diffusion-Training/...
{ "modelfile_path": "D:\\Fooocus\\models\\checkpoints", "lorafile_path": "D:\\Fooocus\\models\\loras", "vae_approx_path": "D:\\Fooocus\\models\\vae_approx", "upscale_models_path": "D:\\Fooocus\\models\\upscale_models", "inpaint_models_path": "D:\\Fooocus\\models\\inpai...
00:50:24-776948 ERROR Training failed / 训练失败 训练的配置,model_train_type = "sd-lora" pretrained_model_name_or_path = "/root/autodl-fs/SDXL1.0/sd_xl_base_1.0.safetensors" v2 = false train_data_dir = "/root/autodl-fs/pre1024" ...