Use mina ashido on your prompt, this was trained on this collab: https://colab.research.google.com/drive/1bFX0pZczeApeFadrz1AdOb5TDdet2U0Z?usp=sharing

!accelerate launch \

--num_cpu_threads_per_process 8 train_network.py \

--network_module=networks.lora \

--pretrained_model_name_or_path="/content/model/nai.ckpt" \

--train_data_dir="/content/drive/MyDrive/sd/dataset/sincos" \

--reg_data_dir="/content/drive/MyDrive/sd/dataset/sincos_reg" \

--output_dir="/content/drive/MyDrive/sd/stable-diffusion-webui/models/lora/" \

--caption_extension=".txt" \

--prior_loss_weight=1 \

--resolution=768 \

--enable_bucket \

--min_bucket_reso=512 \

--max_bucket_reso=1152 \

--train_batch_size=3 \

--learning_rate=1e-4 \

--unet_lr=1.5e-4 \

--text_encoder_lr=1.5e-5 \

# --max_train_steps=8010 \

--mixed_precision="fp16" \

--save_precision="fp16" \

--use_8bit_adam \

--xformers \

--max_train_epochs=8\

--save_every_n_epochs=1\

--save_model_as=safetensors \

--clip_skip=2 \

--seed=23 \

--network_dim=128 \

--network_apha=128 \

--max_token_length=225 \

--cache_latents \

--lr_scheduler="cosine_with_restarts" \

--output_name="minaashido" \

--shuffle_caption \

# --keep_tokens=1 \

# --lr_warmup_steps=$lr_warmup_steps \