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Kaggle_SDXL_Base_DreamBooth.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:907d590b549e68e459505eaa39ee4f6e2e8ef01ce01c5279f4b4ce5d2ba18825
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size 6938040702
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Kaggle_SDXL_Base_DreamBooth_20240717-212556.json
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"output_dir": "/kaggle/temp/models",
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"output_name": "Kaggle_SDXL_Base_DreamBooth",
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}
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config_dreambooth-20240717-212330.toml
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bucket_no_upscale = true
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bucket_reso_steps = 64
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cache_latents = true
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cache_latents_to_disk = true
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clip_skip = 1
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dynamo_backend = "no"
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epoch = 1
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full_fp16 = true
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gradient_accumulation_steps = 1
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gradient_checkpointing = true
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huber_c = 0.1
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huber_schedule = "snr"
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learning_rate = 1e-5
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learning_rate_te1 = 3e-6
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logging_dir = "/kaggle/working/outputs/log"
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loss_type = "l2"
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lr_scheduler = "constant"
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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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max_bucket_reso = 2048
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max_data_loader_n_workers = 0
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max_timestep = 1000
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max_token_length = 75
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max_train_steps = 800
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min_bucket_reso = 256
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mixed_precision = "fp16"
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noise_offset_type = "Original"
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optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False", "weight_decay=0.01",]
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optimizer_type = "Adafactor"
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output_dir = "/kaggle/temp/models"
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output_name = "Kaggle_SDXL_Base_DreamBooth"
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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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reg_data_dir = "/kaggle/working/outputs/reg"
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resolution = "1024,1024"
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sample_prompts = "/kaggle/temp/models/prompt.txt"
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sample_sampler = "euler_a"
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save_every_n_epochs = 1
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save_every_n_steps = 2251
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save_model_as = "safetensors"
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save_precision = "fp16"
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train_batch_size = 2
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train_data_dir = "/kaggle/working/outputs/img"
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vae = "stabilityai/sdxl-vae"
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vae_batch_size = 4
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xformers = true
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config_dreambooth-20240717-212517.toml
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bucket_no_upscale = true
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bucket_reso_steps = 64
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cache_latents = true
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cache_latents_to_disk = true
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clip_skip = 1
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dynamo_backend = "no"
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epoch = 1
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full_fp16 = true
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gradient_accumulation_steps = 1
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gradient_checkpointing = true
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huber_c = 0.1
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huber_schedule = "snr"
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learning_rate = 1e-5
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learning_rate_te1 = 3e-6
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logging_dir = "/kaggle/working/outputs/log"
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loss_type = "l2"
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lr_scheduler = "constant"
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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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max_bucket_reso = 2048
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max_data_loader_n_workers = 0
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max_timestep = 1000
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max_token_length = 75
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max_train_steps = 800
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min_bucket_reso = 256
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mixed_precision = "fp16"
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noise_offset_type = "Original"
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optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False", "weight_decay=0.01",]
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optimizer_type = "Adafactor"
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output_dir = "/kaggle/temp/models"
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output_name = "Kaggle_SDXL_Base_DreamBooth"
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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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reg_data_dir = "/kaggle/working/outputs/reg"
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resolution = "1024,1024"
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sample_prompts = "/kaggle/temp/models/prompt.txt"
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sample_sampler = "euler_a"
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39 |
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save_every_n_epochs = 1
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save_every_n_steps = 2251
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save_model_as = "safetensors"
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save_precision = "fp16"
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train_batch_size = 2
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train_data_dir = "/kaggle/working/outputs/img"
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vae = "stabilityai/sdxl-vae"
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vae_batch_size = 4
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xformers = true
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config_dreambooth-20240717-212556.toml
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bucket_no_upscale = true
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bucket_reso_steps = 64
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3 |
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cache_latents = true
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4 |
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cache_latents_to_disk = true
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5 |
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clip_skip = 1
|
6 |
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dynamo_backend = "no"
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7 |
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epoch = 1
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8 |
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full_fp16 = true
|
9 |
+
gradient_accumulation_steps = 1
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10 |
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gradient_checkpointing = true
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11 |
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huber_c = 0.1
|
12 |
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huber_schedule = "snr"
|
13 |
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learning_rate = 1e-5
|
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learning_rate_te1 = 3e-6
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15 |
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logging_dir = "/kaggle/working/outputs/log"
|
16 |
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loss_type = "l2"
|
17 |
+
lr_scheduler = "constant"
|
18 |
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lr_scheduler_args = []
|
19 |
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lr_scheduler_num_cycles = 1
|
20 |
+
lr_scheduler_power = 1
|
21 |
+
max_bucket_reso = 2048
|
22 |
+
max_data_loader_n_workers = 0
|
23 |
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max_timestep = 1000
|
24 |
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max_token_length = 75
|
25 |
+
max_train_steps = 800
|
26 |
+
min_bucket_reso = 256
|
27 |
+
mixed_precision = "fp16"
|
28 |
+
noise_offset_type = "Original"
|
29 |
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optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False", "weight_decay=0.01",]
|
30 |
+
optimizer_type = "Adafactor"
|
31 |
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output_dir = "/kaggle/temp/models"
|
32 |
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output_name = "Kaggle_SDXL_Base_DreamBooth"
|
33 |
+
pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"
|
34 |
+
prior_loss_weight = 1
|
35 |
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reg_data_dir = "/kaggle/working/outputs/reg"
|
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resolution = "1024,1024"
|
37 |
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sample_prompts = "/kaggle/temp/models/prompt.txt"
|
38 |
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sample_sampler = "euler_a"
|
39 |
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save_every_n_epochs = 1
|
40 |
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save_every_n_steps = 2251
|
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save_model_as = "safetensors"
|
42 |
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save_precision = "fp16"
|
43 |
+
train_batch_size = 2
|
44 |
+
train_data_dir = "/kaggle/working/outputs/img"
|
45 |
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vae = "stabilityai/sdxl-vae"
|
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vae_batch_size = 4
|
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xformers = true
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prompt.txt
CHANGED
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< photo of khalid man>
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