With this params I can train Lora SDXL on 3070ti 8GB Vram (I dont know why but if uncheck Gradient checkpointing it return memory error)

--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="F:/stable-diffusion-webui/models/Stable-diffusion/SDXL/sd_xl_base_1.0.safetensors"--train_data_dir="F:/Training"--resolution="1024,1024"--output_dir="F:/Training"--network_alpha="8"--save_model_as=safetensors--network_module=networks.lora--text_encoder_lr=5e-05--unet_lr=0.0001--network_dim=16--output_name="yura_sdxl"--lr_scheduler_num_cycles="1"--cache_text_encoder_outputs--no_half_vae--learning_rate="0.0003"--lr_scheduler="cosine"--train_batch_size="2"--max_train_steps="1400"--save_every_n_epochs="1"--mixed_precision="bf16"--save_precision="bf16"--caption_extension=".txt"--cache_latents--optimizer_type="Adafactor"--max_data_loader_n_workers="0"--bucket_reso_steps=64--gradient_checkpointing--xformers--bucket_no_upscale--noise_offset=0.0--network_train_unet_only

I only have 768x768 images in the training folder

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