feat: upload asahi lora model
Browse files
asahi_config/config_file.toml
CHANGED
@@ -6,7 +6,7 @@ pretrained_model_name_or_path = "/content/pretrained_model/Animefull-final-prune
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[additional_network_arguments]
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no_metadata = false
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unet_lr = 1.0
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text_encoder_lr = 0
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network_module = "networks.lora"
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network_dim = 32
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network_alpha = 32
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@@ -14,10 +14,10 @@ network_train_unet_only = false
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network_train_text_encoder_only = false
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[optimizer_arguments]
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optimizer_type = "
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learning_rate = 1.0
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max_grad_norm = 1.0
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optimizer_args = [ "decouple=True", "weight_decay=0.01", "betas=0.9,0.99",]
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lr_scheduler = "constant"
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lr_warmup_steps = 0
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@@ -30,12 +30,12 @@ vae_batch_size = 4
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output_dir = "/content/LoRA/output"
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output_name = "asahi"
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save_precision = "fp16"
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save_every_n_epochs =
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train_batch_size = 3
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max_token_length = 225
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mem_eff_attn = false
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xformers = true
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max_train_epochs =
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max_data_loader_n_workers = 8
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persistent_data_loader_workers = true
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seed = 31337
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@@ -48,7 +48,7 @@ log_prefix = "asahi"
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lowram = true
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[sample_prompt_arguments]
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sample_every_n_epochs =
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sample_sampler = "ddim"
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[dreambooth_arguments]
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[additional_network_arguments]
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no_metadata = false
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unet_lr = 1.0
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text_encoder_lr = 1.0
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network_module = "networks.lora"
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network_dim = 32
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network_alpha = 32
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network_train_text_encoder_only = false
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[optimizer_arguments]
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optimizer_type = "Prodigy"
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learning_rate = 1.0
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max_grad_norm = 1.0
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optimizer_args = [ "decouple=True", "weight_decay=0.01", "d_coef=2", "use_bias_correction=True", "safeguard_warmup=True", "betas=0.9,0.99",]
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lr_scheduler = "constant"
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lr_warmup_steps = 0
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output_dir = "/content/LoRA/output"
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output_name = "asahi"
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save_precision = "fp16"
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+
save_every_n_epochs = 10
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train_batch_size = 3
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max_token_length = 225
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mem_eff_attn = false
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xformers = true
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max_train_epochs = 100
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max_data_loader_n_workers = 8
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persistent_data_loader_workers = true
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seed = 31337
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lowram = true
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[sample_prompt_arguments]
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sample_every_n_epochs = 10
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sample_sampler = "ddim"
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[dreambooth_arguments]
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asahi_config/dataset_config.toml
CHANGED
@@ -10,7 +10,7 @@ color_aug = false
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[[datasets.subsets]]
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image_dir = "/content/LoRA/train_data"
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class_tokens = "mksks"
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num_repeats =
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[general]
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[[datasets.subsets]]
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image_dir = "/content/LoRA/train_data"
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class_tokens = "mksks"
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num_repeats = 2
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[general]
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