Upload config.toml with huggingface_hub
Browse files- config.toml +55 -0
config.toml
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bucket_no_upscale = true
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| 2 |
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bucket_reso_steps = 64
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cache_latents = true
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caption_extension = ".txt"
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clip_skip = 1
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dynamo_backend = "no"
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enable_bucket = true
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epoch = 20
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gradient_accumulation_steps = 1
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huber_c = 0.1
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huber_schedule = "snr"
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huggingface_repo_id = "BKM1804/lora_cluster"
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huggingface_repo_type = "model"
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huggingface_repo_visibility = "public"
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learning_rate = 0.0001
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loss_type = "l2"
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lr_scheduler = "cosine_with_restarts"
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lr_scheduler_args = []
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lr_scheduler_num_cycles = 1
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lr_scheduler_power = 1
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lr_warmup_steps = 300
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max_bucket_reso = 2048
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max_data_loader_n_workers = 0
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max_grad_norm = 1
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max_timestep = 1000
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max_token_length = 75
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max_train_steps = 3000
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min_bucket_reso = 256
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min_snr_gamma = 5
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mixed_precision = "fp16"
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multires_noise_discount = 0.3
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network_alpha = 128
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network_args = []
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network_dim = 128
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network_module = "networks.lora"
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no_half_vae = true
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noise_offset = 0.1
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noise_offset_type = "Original"
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optimizer_args = []
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optimizer_type = "AdamW"
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output_dir = "/workspace/kohya_ss/outputs"
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output_name = "last"
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pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"
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prior_loss_weight = 1
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resolution = "512"
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sample_prompts = "/workspace/kohya_ss/outputs/prompt.txt"
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sample_sampler = "euler_a"
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save_every_n_epochs = 1
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save_model_as = "safetensors"
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save_precision = "fp16"
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text_encoder_lr = 4e-5
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train_batch_size = 1
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train_data_dir = "/workspace/data/img"
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unet_lr = 0.0001
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xformers = true
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