feat: upload sdxl_lora lora model

sdxl_lora_config/config_file.toml

@@ -0,0 +1,77 @@
+[sdxl_arguments]
+cache_text_encoder_outputs = false
+no_half_vae = true
+min_timestep = 0
+max_timestep = 1000
+shuffle_caption = true
+lowram = true
+
+[model_arguments]
+pretrained_model_name_or_path = "cagliostrolab/animagine-xl-3.0-base"
+vae = "/content/vae/sdxl_vae.safetensors"
+
+[dataset_arguments]
+debug_dataset = false
+in_json = "/content/LoRA/meta_lat.json"
+train_data_dir = "/content/LoRA/train_data"
+dataset_repeats = 1
+keep_tokens = 1
+resolution = "1024,1024"
+color_aug = false
+token_warmup_min = 1
+token_warmup_step = 0
+
+[training_arguments]
+output_dir = "/content/LoRA/output/shu"
+output_name = "shu"
+save_precision = "fp16"
+save_every_n_epochs = 1
+train_batch_size = 4
+max_token_length = 225
+mem_eff_attn = false
+sdpa = true
+xformers = false
+max_train_epochs = 6
+max_data_loader_n_workers = 8
+persistent_data_loader_workers = true
+gradient_checkpointing = true
+gradient_accumulation_steps = 1
+mixed_precision = "fp16"
+
+[logging_arguments]
+log_with = "tensorboard"
+logging_dir = "/content/LoRA/logs"
+log_prefix = "shu"
+
+[sample_prompt_arguments]
+sample_every_n_epochs = 1
+sample_sampler = "euler_a"
+
+[saving_arguments]
+save_model_as = "safetensors"
+
+[optimizer_arguments]
+optimizer_type = "prodigy"
+learning_rate = 1
+max_grad_norm = 0
+optimizer_args = [ "decouple=True","weight_decay=0.01","d_coef=2","use_bias_correction=True","safeguard_warmup=True","betas=0.9,0.99"]
+lr_scheduler = "constant_with_warmup"
+lr_warmup_steps = 100
+
+[additional_network_arguments]
+no_metadata = false
+network_module = "networks.lora"
+network_dim = 16
+network_alpha = 1
+network_args = []
+network_train_unet_only = true
+
+[advanced_training_config]
+save_state = false
+save_last_n_epochs_state = false
+multires_noise_iterations = 6
+multires_noise_discount = 0.3
+caption_dropout_rate = 0
+caption_tag_dropout_rate = 0.5
+caption_dropout_every_n_epochs = 0
+min_snr_gamma = 5

sdxl_lora_config/sample_prompt.toml

@@ -0,0 +1,9 @@
+[prompt]
+negative_prompt = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, "
+width = 1024
+height = 1024
+scale = 12
+sample_steps = 28
+[[prompt.subset]]
+prompt = "masterpiece, best quality, masterpiece,best quality,shu,1girl"
+