feat: upload matsumoto-sarina lora model

matsumoto-sarina_config/config_file.toml

@@ -5,35 +5,25 @@ pretrained_model_name_or_path = "/content/pretrained_model/Animefull-final-prune
 
 [additional_network_arguments]
 no_metadata = false
-unet_lr = 0.00015
-text_encoder_lr = 1.5e-5
+unet_lr = 0.0001
+text_encoder_lr = 5e-5
 network_module = "networks.lora"
-network_dim = 128
-network_alpha = 64
+network_dim = 64
+network_alpha = 32
 network_train_unet_only = false
 network_train_text_encoder_only = false
 
 [optimizer_arguments]
 optimizer_type = "AdamW8bit"
-learning_rate = 0.00015
+learning_rate = 0.0001
 max_grad_norm = 1.0
 lr_scheduler = "constant_with_warmup"
 lr_warmup_steps = 5
 
 [dataset_arguments]
+cache_latents = true
 debug_dataset = false
-in_json = "/content/LoRA/meta_lat.json"
-train_data_dir = "/content/LoRA/train_data"
-dataset_repeats = 27
-shuffle_caption = true
-keep_tokens = 0
-resolution = "512,512"
-caption_dropout_rate = 0
-caption_tag_dropout_rate = 0
-caption_dropout_every_n_epochs = 0
-color_aug = false
-token_warmup_min = 1
-token_warmup_step = 0
+vae_batch_size = 4
 
 [training_arguments]
 output_dir = "/content/LoRA/output"
@@ -59,5 +49,8 @@ lowram = true
 sample_every_n_epochs = 999999
 sample_sampler = "ddim"
 
+[dreambooth_arguments]
+prior_loss_weight = 1.0
+
 [saving_arguments]
 save_model_as = "safetensors"

matsumoto-sarina_config/dataset_config.toml

@@ -0,0 +1,22 @@
+[[datasets]]
+resolution = 640
+min_bucket_reso = 256
+max_bucket_reso = 1024
+caption_dropout_rate = 0
+caption_tag_dropout_rate = 0
+caption_dropout_every_n_epochs = 0
+flip_aug = false
+color_aug = false
+[[datasets.subsets]]
+image_dir = "/content/LoRA/train_data"
+class_tokens = "matsumoto_sarina"
+num_repeats = 27
+
+
+[general]
+enable_bucket = true
+caption_extension = ".txt"
+shuffle_caption = true
+keep_tokens = 1
+bucket_reso_steps = 64
+bucket_no_upscale = false