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- .gitattributes +33 -0
- config_lora-20250602-145848.toml +48 -0
- config_lora-20250602-145929.toml +48 -0
- config_lora-20250602-150005.toml +48 -0
- config_lora-20250602-150102.toml +48 -0
- config_lora-20250602-150232.toml +49 -0
- config_lora-20250602-150344.toml +49 -0
- config_lora-20250602-150626.toml +49 -0
- config_lora-20250602-150707.toml +49 -0
- config_lora-20250602-151250.toml +49 -0
- config_lora-20250602-151500.toml +50 -0
- config_lora-20250602-151638.toml +50 -0
- config_lora-20250602-151841.toml +50 -0
- config_lora-20250602-152328.toml +51 -0
- config_lora-20250602-152659.toml +51 -0
- config_lora-20250602-152748.toml +51 -0
- config_lora-20250602-152812.toml +50 -0
- config_lora-20250602-152843.toml +51 -0
- config_lora-20250602-153053.toml +51 -0
- config_lora-20250602-153250.toml +49 -0
- config_lora-20250602-153310.toml +49 -0
- config_lora-20250602-153339.toml +49 -0
- config_lora-20250602-153522.toml +49 -0
- config_lora-20250602-155358.toml +51 -0
- img/100_Lena person/1.png +3 -0
- img/100_Lena person/1.txt +1 -0
- img/100_Lena person/10.png +3 -0
- img/100_Lena person/10.txt +1 -0
- img/100_Lena person/11.png +3 -0
- img/100_Lena person/11.txt +1 -0
- img/100_Lena person/12.png +3 -0
- img/100_Lena person/12.txt +1 -0
- img/100_Lena person/13.png +3 -0
- img/100_Lena person/13.txt +1 -0
- img/100_Lena person/14.png +3 -0
- img/100_Lena person/14.txt +1 -0
- img/100_Lena person/15.png +3 -0
- img/100_Lena person/15.txt +1 -0
- img/100_Lena person/2.png +3 -0
- img/100_Lena person/2.txt +1 -0
- img/100_Lena person/3.png +3 -0
- img/100_Lena person/3.txt +1 -0
- img/100_Lena person/4.png +3 -0
- img/100_Lena person/4.txt +1 -0
- img/100_Lena person/5.png +3 -0
- img/100_Lena person/5.txt +1 -0
- img/100_Lena person/6.png +3 -0
- img/100_Lena person/6.txt +1 -0
- img/100_Lena person/7.png +3 -0
- img/100_Lena person/7.txt +1 -0
.gitattributes
CHANGED
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@@ -33,3 +33,36 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/1.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/10.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/11.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/12.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/13.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/14.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/15.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/2.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/3.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/4.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/5.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/6.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/7.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/8.png filter=lfs diff=lfs merge=lfs -text
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img/100_Lena[[:space:]]person/9.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000001_00_20250602162805.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000001_00_20250602164004.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000001_01_20250602164008.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000001_02_20250602162813.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000001_02_20250602164012.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000002_00_20250602164323.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000002_01_20250602164328.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000002_02_20250602164332.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000003_00_20250602164632.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000003_01_20250602164636.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000004_00_20250602164941.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000004_01_20250602164945.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000004_02_20250602164949.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000005_00_20250602165042.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000005_01_20250602165046.png filter=lfs diff=lfs merge=lfs -text
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model/sample/last_e000005_02_20250602165050.png filter=lfs diff=lfs merge=lfs -text
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config_lora-20250602-145848.toml
ADDED
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@@ -0,0 +1,48 @@
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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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| 4 |
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caption_extension = ".txt"
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clip_skip = 1
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| 6 |
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dynamo_backend = "no"
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enable_bucket = true
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epoch = 1
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| 9 |
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gradient_accumulation_steps = 1
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| 10 |
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huber_c = 0.1
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huber_scale = 1
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huber_schedule = "snr"
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loss_type = "l2"
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| 14 |
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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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| 19 |
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max_data_loader_n_workers = 0
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| 20 |
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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 = 1600
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min_bucket_reso = 512
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mixed_precision = "fp16"
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network_alpha = 16
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network_args = []
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| 28 |
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network_dim = 32
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| 29 |
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network_module = "networks.lora"
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| 30 |
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noise_offset_type = "Original"
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| 31 |
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optimizer_args = []
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| 32 |
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optimizer_type = "DAdaptAdam"
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| 33 |
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output_dir = "/workspace/kohya_ss/outputs"
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| 34 |
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output_name = "last"
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| 35 |
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pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
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| 36 |
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prior_loss_weight = 1
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| 37 |
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resolution = "512,512"
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| 38 |
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sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
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| 39 |
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sample_sampler = "euler_a"
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| 40 |
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save_every_n_epochs = 1
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| 41 |
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save_model_as = "safetensors"
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| 42 |
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save_precision = "fp16"
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| 43 |
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text_encoder_lr = [ 4.5e-5, 4.5e-5,]
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| 44 |
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train_batch_size = 1
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| 45 |
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train_data_dir = "/workspace/kohya_ss/dataset/images"
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| 46 |
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unet_lr = 0.0001
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| 47 |
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wandb_run_name = "last"
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| 48 |
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xformers = true
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config_lora-20250602-145929.toml
ADDED
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@@ -0,0 +1,48 @@
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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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| 3 |
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cache_latents = true
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| 4 |
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caption_extension = ".txt"
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| 5 |
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clip_skip = 1
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| 6 |
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dynamo_backend = "no"
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| 7 |
+
enable_bucket = true
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| 8 |
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epoch = 1
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| 9 |
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gradient_accumulation_steps = 1
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| 10 |
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huber_c = 0.1
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| 11 |
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huber_scale = 1
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| 12 |
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huber_schedule = "snr"
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| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
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| 15 |
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lr_scheduler_args = []
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| 16 |
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lr_scheduler_num_cycles = 1
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| 17 |
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lr_scheduler_power = 1
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| 18 |
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max_bucket_reso = 2048
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| 19 |
+
max_data_loader_n_workers = 0
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| 20 |
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max_grad_norm = 1
|
| 21 |
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max_timestep = 1000
|
| 22 |
+
max_token_length = 75
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| 23 |
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max_train_steps = 1600
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| 24 |
+
min_bucket_reso = 512
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| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
noise_offset_type = "Original"
|
| 31 |
+
optimizer_args = []
|
| 32 |
+
optimizer_type = "DAdaptAdam"
|
| 33 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 34 |
+
output_name = "last"
|
| 35 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 36 |
+
prior_loss_weight = 1
|
| 37 |
+
resolution = "512,512"
|
| 38 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 39 |
+
sample_sampler = "euler_a"
|
| 40 |
+
save_every_n_epochs = 1
|
| 41 |
+
save_model_as = "safetensors"
|
| 42 |
+
save_precision = "fp16"
|
| 43 |
+
text_encoder_lr = [ 4.5e-5, 4.5e-5,]
|
| 44 |
+
train_batch_size = 1
|
| 45 |
+
train_data_dir = "/workspace/kohya_ss/img/40_Lena person"
|
| 46 |
+
unet_lr = 0.0001
|
| 47 |
+
wandb_run_name = "last"
|
| 48 |
+
xformers = true
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config_lora-20250602-150005.toml
ADDED
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@@ -0,0 +1,48 @@
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| 1 |
+
bucket_no_upscale = true
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| 2 |
+
bucket_reso_steps = 64
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| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
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| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
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| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
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| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 512
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
noise_offset_type = "Original"
|
| 31 |
+
optimizer_args = []
|
| 32 |
+
optimizer_type = "DAdaptAdam"
|
| 33 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 34 |
+
output_name = "last"
|
| 35 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 36 |
+
prior_loss_weight = 1
|
| 37 |
+
resolution = "512,512"
|
| 38 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 39 |
+
sample_sampler = "euler_a"
|
| 40 |
+
save_every_n_epochs = 1
|
| 41 |
+
save_model_as = "safetensors"
|
| 42 |
+
save_precision = "fp16"
|
| 43 |
+
text_encoder_lr = [ 4.5e-5, 4.5e-5,]
|
| 44 |
+
train_batch_size = 1
|
| 45 |
+
train_data_dir = "/workspace/kohya_ss/img/40_Lena person"
|
| 46 |
+
unet_lr = 0.0001
|
| 47 |
+
wandb_run_name = "last"
|
| 48 |
+
xformers = true
|
config_lora-20250602-150102.toml
ADDED
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@@ -0,0 +1,48 @@
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bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 512
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
noise_offset_type = "Original"
|
| 31 |
+
optimizer_args = []
|
| 32 |
+
optimizer_type = "AdamW8bit"
|
| 33 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 34 |
+
output_name = "last"
|
| 35 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 36 |
+
prior_loss_weight = 1
|
| 37 |
+
resolution = "512,512"
|
| 38 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 39 |
+
sample_sampler = "euler_a"
|
| 40 |
+
save_every_n_epochs = 1
|
| 41 |
+
save_model_as = "safetensors"
|
| 42 |
+
save_precision = "fp16"
|
| 43 |
+
text_encoder_lr = [ 4.5e-5, 4.5e-5,]
|
| 44 |
+
train_batch_size = 4
|
| 45 |
+
train_data_dir = "/workspace/kohya_ss/img/40_Lena person"
|
| 46 |
+
unet_lr = 0.0001
|
| 47 |
+
wandb_run_name = "last"
|
| 48 |
+
xformers = true
|
config_lora-20250602-150232.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img/40_Lena"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-150344.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img/40_Lena"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-150626.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img/40_Lena/"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-150707.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img/40_Lena"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-151250.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img/10_Lena person"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-151500.toml
ADDED
|
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_epochs = 10
|
| 24 |
+
max_train_steps = 1600
|
| 25 |
+
min_bucket_reso = 64
|
| 26 |
+
mixed_precision = "fp16"
|
| 27 |
+
network_alpha = 16
|
| 28 |
+
network_args = []
|
| 29 |
+
network_dim = 32
|
| 30 |
+
network_module = "networks.lora"
|
| 31 |
+
network_train_unet_only = true
|
| 32 |
+
noise_offset_type = "Original"
|
| 33 |
+
optimizer_args = []
|
| 34 |
+
optimizer_type = "AdamW8bit"
|
| 35 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 36 |
+
output_name = "last"
|
| 37 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 38 |
+
prior_loss_weight = 1
|
| 39 |
+
resolution = "512,512"
|
| 40 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 41 |
+
sample_sampler = "euler_a"
|
| 42 |
+
save_every_n_epochs = 1
|
| 43 |
+
save_model_as = "safetensors"
|
| 44 |
+
save_precision = "fp16"
|
| 45 |
+
text_encoder_lr = []
|
| 46 |
+
train_batch_size = 4
|
| 47 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person"
|
| 48 |
+
unet_lr = 0.0001
|
| 49 |
+
wandb_run_name = "last"
|
| 50 |
+
xformers = true
|
config_lora-20250602-151638.toml
ADDED
|
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_epochs = 10
|
| 24 |
+
max_train_steps = 1600
|
| 25 |
+
min_bucket_reso = 64
|
| 26 |
+
mixed_precision = "fp16"
|
| 27 |
+
network_alpha = 16
|
| 28 |
+
network_args = []
|
| 29 |
+
network_dim = 32
|
| 30 |
+
network_module = "networks.lora"
|
| 31 |
+
network_train_unet_only = true
|
| 32 |
+
noise_offset_type = "Original"
|
| 33 |
+
optimizer_args = []
|
| 34 |
+
optimizer_type = "AdamW8bit"
|
| 35 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 36 |
+
output_name = "last"
|
| 37 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 38 |
+
prior_loss_weight = 1
|
| 39 |
+
resolution = "512,512"
|
| 40 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 41 |
+
sample_sampler = "euler_a"
|
| 42 |
+
save_every_n_epochs = 1
|
| 43 |
+
save_model_as = "safetensors"
|
| 44 |
+
save_precision = "fp16"
|
| 45 |
+
text_encoder_lr = []
|
| 46 |
+
train_batch_size = 4
|
| 47 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person"
|
| 48 |
+
unet_lr = 0.0001
|
| 49 |
+
wandb_run_name = "last"
|
| 50 |
+
xformers = true
|
config_lora-20250602-151841.toml
ADDED
|
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_epochs = 10
|
| 24 |
+
max_train_steps = 1600
|
| 25 |
+
min_bucket_reso = 64
|
| 26 |
+
mixed_precision = "fp16"
|
| 27 |
+
network_alpha = 16
|
| 28 |
+
network_args = []
|
| 29 |
+
network_dim = 32
|
| 30 |
+
network_module = "networks.lora"
|
| 31 |
+
network_train_unet_only = true
|
| 32 |
+
noise_offset_type = "Original"
|
| 33 |
+
optimizer_args = []
|
| 34 |
+
optimizer_type = "AdamW8bit"
|
| 35 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 36 |
+
output_name = "last"
|
| 37 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 38 |
+
prior_loss_weight = 1
|
| 39 |
+
resolution = "512,512"
|
| 40 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 41 |
+
sample_sampler = "euler_a"
|
| 42 |
+
save_every_n_epochs = 1
|
| 43 |
+
save_model_as = "safetensors"
|
| 44 |
+
save_precision = "fp16"
|
| 45 |
+
text_encoder_lr = []
|
| 46 |
+
train_batch_size = 4
|
| 47 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person"
|
| 48 |
+
unet_lr = 0.0001
|
| 49 |
+
wandb_run_name = "last"
|
| 50 |
+
xformers = true
|
config_lora-20250602-152328.toml
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "cosine"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
lr_warmup_steps = 0.1
|
| 19 |
+
max_bucket_reso = 2048
|
| 20 |
+
max_data_loader_n_workers = 0
|
| 21 |
+
max_grad_norm = 1
|
| 22 |
+
max_timestep = 1000
|
| 23 |
+
max_token_length = 75
|
| 24 |
+
max_train_epochs = 10
|
| 25 |
+
max_train_steps = 1600
|
| 26 |
+
min_bucket_reso = 64
|
| 27 |
+
mixed_precision = "fp16"
|
| 28 |
+
network_alpha = 16
|
| 29 |
+
network_args = []
|
| 30 |
+
network_dim = 32
|
| 31 |
+
network_module = "networks.lora"
|
| 32 |
+
network_train_unet_only = true
|
| 33 |
+
noise_offset_type = "Original"
|
| 34 |
+
optimizer_args = []
|
| 35 |
+
optimizer_type = "AdamW8bit"
|
| 36 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 37 |
+
output_name = "last"
|
| 38 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 39 |
+
prior_loss_weight = 1
|
| 40 |
+
resolution = "512,512"
|
| 41 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 42 |
+
sample_sampler = "euler_a"
|
| 43 |
+
save_every_n_epochs = 1
|
| 44 |
+
save_model_as = "safetensors"
|
| 45 |
+
save_precision = "fp16"
|
| 46 |
+
text_encoder_lr = []
|
| 47 |
+
train_batch_size = 4
|
| 48 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person"
|
| 49 |
+
unet_lr = 0.0001
|
| 50 |
+
wandb_run_name = "last"
|
| 51 |
+
xformers = true
|
config_lora-20250602-152659.toml
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "cosine"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
lr_warmup_steps = 0.1
|
| 19 |
+
max_bucket_reso = 2048
|
| 20 |
+
max_data_loader_n_workers = 0
|
| 21 |
+
max_grad_norm = 1
|
| 22 |
+
max_timestep = 1000
|
| 23 |
+
max_token_length = 75
|
| 24 |
+
max_train_epochs = 10
|
| 25 |
+
max_train_steps = 1600
|
| 26 |
+
min_bucket_reso = 64
|
| 27 |
+
mixed_precision = "fp16"
|
| 28 |
+
network_alpha = 16
|
| 29 |
+
network_args = []
|
| 30 |
+
network_dim = 32
|
| 31 |
+
network_module = "networks.lora"
|
| 32 |
+
network_train_unet_only = true
|
| 33 |
+
noise_offset_type = "Original"
|
| 34 |
+
optimizer_args = []
|
| 35 |
+
optimizer_type = "AdamW8bit"
|
| 36 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 37 |
+
output_name = "last"
|
| 38 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 39 |
+
prior_loss_weight = 1
|
| 40 |
+
resolution = "512,512"
|
| 41 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 42 |
+
sample_sampler = "euler_a"
|
| 43 |
+
save_every_n_epochs = 1
|
| 44 |
+
save_model_as = "safetensors"
|
| 45 |
+
save_precision = "fp16"
|
| 46 |
+
text_encoder_lr = []
|
| 47 |
+
train_batch_size = 4
|
| 48 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person"
|
| 49 |
+
unet_lr = 0.0001
|
| 50 |
+
wandb_run_name = "last"
|
| 51 |
+
xformers = true
|
config_lora-20250602-152748.toml
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "cosine"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
lr_warmup_steps = 0.1
|
| 19 |
+
max_bucket_reso = 2048
|
| 20 |
+
max_data_loader_n_workers = 0
|
| 21 |
+
max_grad_norm = 1
|
| 22 |
+
max_timestep = 1000
|
| 23 |
+
max_token_length = 75
|
| 24 |
+
max_train_epochs = 10
|
| 25 |
+
max_train_steps = 1600
|
| 26 |
+
min_bucket_reso = 64
|
| 27 |
+
mixed_precision = "fp16"
|
| 28 |
+
network_alpha = 16
|
| 29 |
+
network_args = []
|
| 30 |
+
network_dim = 32
|
| 31 |
+
network_module = "networks.lora"
|
| 32 |
+
network_train_unet_only = true
|
| 33 |
+
noise_offset_type = "Original"
|
| 34 |
+
optimizer_args = []
|
| 35 |
+
optimizer_type = "AdamW8bit"
|
| 36 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 37 |
+
output_name = "last"
|
| 38 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 39 |
+
prior_loss_weight = 1
|
| 40 |
+
resolution = "512,512"
|
| 41 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 42 |
+
sample_sampler = "euler_a"
|
| 43 |
+
save_every_n_epochs = 1
|
| 44 |
+
save_model_as = "safetensors"
|
| 45 |
+
save_precision = "fp16"
|
| 46 |
+
text_encoder_lr = []
|
| 47 |
+
train_batch_size = 4
|
| 48 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person/images"
|
| 49 |
+
unet_lr = 0.0001
|
| 50 |
+
wandb_run_name = "last"
|
| 51 |
+
xformers = true
|
config_lora-20250602-152812.toml
ADDED
|
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_epochs = 10
|
| 24 |
+
max_train_steps = 1600
|
| 25 |
+
min_bucket_reso = 64
|
| 26 |
+
mixed_precision = "fp16"
|
| 27 |
+
network_alpha = 16
|
| 28 |
+
network_args = []
|
| 29 |
+
network_dim = 32
|
| 30 |
+
network_module = "networks.lora"
|
| 31 |
+
network_train_unet_only = true
|
| 32 |
+
noise_offset_type = "Original"
|
| 33 |
+
optimizer_args = []
|
| 34 |
+
optimizer_type = "AdamW8bit"
|
| 35 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 36 |
+
output_name = "last"
|
| 37 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 38 |
+
prior_loss_weight = 1
|
| 39 |
+
resolution = "512,512"
|
| 40 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 41 |
+
sample_sampler = "euler_a"
|
| 42 |
+
save_every_n_epochs = 1
|
| 43 |
+
save_model_as = "safetensors"
|
| 44 |
+
save_precision = "fp16"
|
| 45 |
+
text_encoder_lr = []
|
| 46 |
+
train_batch_size = 4
|
| 47 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person/images"
|
| 48 |
+
unet_lr = 0.0001
|
| 49 |
+
wandb_run_name = "last"
|
| 50 |
+
xformers = true
|
config_lora-20250602-152843.toml
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_epochs = 10
|
| 24 |
+
max_train_steps = 1600
|
| 25 |
+
min_bucket_reso = 64
|
| 26 |
+
mixed_precision = "fp16"
|
| 27 |
+
network_alpha = 16
|
| 28 |
+
network_args = []
|
| 29 |
+
network_dim = 32
|
| 30 |
+
network_module = "networks.lora"
|
| 31 |
+
network_train_unet_only = true
|
| 32 |
+
noise_offset_type = "Original"
|
| 33 |
+
optimizer_args = []
|
| 34 |
+
optimizer_type = "AdamW8bit"
|
| 35 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 36 |
+
output_name = "last"
|
| 37 |
+
pretrained_model_name_or_path = "stabilityai/stable-diffusion-2-base"
|
| 38 |
+
prior_loss_weight = 1
|
| 39 |
+
resolution = "512,512"
|
| 40 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 41 |
+
sample_sampler = "euler_a"
|
| 42 |
+
save_every_n_epochs = 1
|
| 43 |
+
save_model_as = "safetensors"
|
| 44 |
+
save_precision = "fp16"
|
| 45 |
+
text_encoder_lr = []
|
| 46 |
+
train_batch_size = 4
|
| 47 |
+
train_data_dir = "/workspace/kohya_ss/img/10_Lena person/images"
|
| 48 |
+
unet_lr = 0.0001
|
| 49 |
+
v2 = true
|
| 50 |
+
wandb_run_name = "last"
|
| 51 |
+
xformers = true
|
config_lora-20250602-153053.toml
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_epochs = 10
|
| 24 |
+
max_train_steps = 1600
|
| 25 |
+
min_bucket_reso = 64
|
| 26 |
+
mixed_precision = "fp16"
|
| 27 |
+
network_alpha = 16
|
| 28 |
+
network_args = []
|
| 29 |
+
network_dim = 32
|
| 30 |
+
network_module = "networks.lora"
|
| 31 |
+
network_train_unet_only = true
|
| 32 |
+
noise_offset_type = "Original"
|
| 33 |
+
optimizer_args = []
|
| 34 |
+
optimizer_type = "AdamW8bit"
|
| 35 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 36 |
+
output_name = "last"
|
| 37 |
+
pretrained_model_name_or_path = "stabilityai/stable-diffusion-2-base"
|
| 38 |
+
prior_loss_weight = 1
|
| 39 |
+
resolution = "512,512"
|
| 40 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 41 |
+
sample_sampler = "euler_a"
|
| 42 |
+
save_every_n_epochs = 1
|
| 43 |
+
save_model_as = "safetensors"
|
| 44 |
+
save_precision = "fp16"
|
| 45 |
+
text_encoder_lr = []
|
| 46 |
+
train_batch_size = 4
|
| 47 |
+
train_data_dir = "/workspace/kohya_ss/img"
|
| 48 |
+
unet_lr = 0.0001
|
| 49 |
+
v2 = true
|
| 50 |
+
wandb_run_name = "last"
|
| 51 |
+
xformers = true
|
config_lora-20250602-153250.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-153310.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-153339.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "coreml-community/coreml-RealismEngineSDXL-v10_SDXL_8bit"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-153522.toml
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "AdamW8bit"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 40 |
+
sample_sampler = "euler_a"
|
| 41 |
+
save_every_n_epochs = 1
|
| 42 |
+
save_model_as = "safetensors"
|
| 43 |
+
save_precision = "fp16"
|
| 44 |
+
text_encoder_lr = []
|
| 45 |
+
train_batch_size = 4
|
| 46 |
+
train_data_dir = "./img"
|
| 47 |
+
unet_lr = 0.0001
|
| 48 |
+
wandb_run_name = "last"
|
| 49 |
+
xformers = true
|
config_lora-20250602-155358.toml
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
bucket_no_upscale = true
|
| 2 |
+
bucket_reso_steps = 64
|
| 3 |
+
cache_latents = true
|
| 4 |
+
caption_extension = ".txt"
|
| 5 |
+
clip_skip = 1
|
| 6 |
+
dynamo_backend = "no"
|
| 7 |
+
enable_bucket = true
|
| 8 |
+
epoch = 1
|
| 9 |
+
gradient_accumulation_steps = 1
|
| 10 |
+
huber_c = 0.1
|
| 11 |
+
huber_scale = 1
|
| 12 |
+
huber_schedule = "snr"
|
| 13 |
+
loss_type = "l2"
|
| 14 |
+
lr_scheduler = "constant"
|
| 15 |
+
lr_scheduler_args = []
|
| 16 |
+
lr_scheduler_num_cycles = 1
|
| 17 |
+
lr_scheduler_power = 1
|
| 18 |
+
max_bucket_reso = 2048
|
| 19 |
+
max_data_loader_n_workers = 0
|
| 20 |
+
max_grad_norm = 1
|
| 21 |
+
max_timestep = 1000
|
| 22 |
+
max_token_length = 75
|
| 23 |
+
max_train_steps = 1600
|
| 24 |
+
min_bucket_reso = 64
|
| 25 |
+
mixed_precision = "fp16"
|
| 26 |
+
network_alpha = 16
|
| 27 |
+
network_args = []
|
| 28 |
+
network_dim = 32
|
| 29 |
+
network_module = "networks.lora"
|
| 30 |
+
network_train_unet_only = true
|
| 31 |
+
noise_offset_type = "Original"
|
| 32 |
+
optimizer_args = []
|
| 33 |
+
optimizer_type = "DAdaptAdam"
|
| 34 |
+
output_dir = "/workspace/kohya_ss/outputs"
|
| 35 |
+
output_name = "last"
|
| 36 |
+
pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"
|
| 37 |
+
prior_loss_weight = 1
|
| 38 |
+
resolution = "512,512"
|
| 39 |
+
sample_every_n_epochs = 1
|
| 40 |
+
sample_every_n_steps = 5
|
| 41 |
+
sample_prompts = "/workspace/kohya_ss/outputs/sample/prompt.txt"
|
| 42 |
+
sample_sampler = "euler_a"
|
| 43 |
+
save_every_n_epochs = 1
|
| 44 |
+
save_model_as = "safetensors"
|
| 45 |
+
save_precision = "bf16"
|
| 46 |
+
text_encoder_lr = []
|
| 47 |
+
train_batch_size = 4
|
| 48 |
+
train_data_dir = "./img"
|
| 49 |
+
unet_lr = 0.0001
|
| 50 |
+
wandb_run_name = "last"
|
| 51 |
+
xformers = true
|
img/100_Lena person/1.png
ADDED
|
Git LFS Details
|
img/100_Lena person/1.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, smile, brown hair, navel, holding, cleavage, brown eyes, medium breasts, sitting, closed mouth, underwear, collarbone, outdoors, day, water, bra, tree, lips, phone, cellphone, nature, smartphone, reflection, holding phone, sports bra, realistic, selfie, river, lake
|
img/100_Lena person/10.png
ADDED
|
Git LFS Details
|
img/100_Lena person/10.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, brown hair, cleavage, brown eyes, medium breasts, underwear, collarbone, upper body, bra, mole, lips, freckles, mole on breast, realistic, pink bra
|
img/100_Lena person/11.png
ADDED
|
Git LFS Details
|
img/100_Lena person/11.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, brown hair, navel, holding, medium breasts, sitting, closed mouth, nipples, green eyes, collarbone, nude, small breasts, indoors, mole, lips, fingernails, chair, phone, piercing, cellphone, tan, smartphone, freckles, tanlines, holding phone, realistic, selfie, office chair
|
img/100_Lena person/12.png
ADDED
|
Git LFS Details
|
img/100_Lena person/12.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, brown hair, black hair, navel, cleavage, brown eyes, medium breasts, collarbone, upper body, outdoors, sky, day, midriff, mole, covered nipples, tree, lips, crop top, tank top, ground vehicle, building, motor vehicle, freckles, mole on breast, city, realistic, car, road, street
|
img/100_Lena person/13.png
ADDED
|
Git LFS Details
|
img/100_Lena person/13.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
long hair, breasts, looking at viewer, multiple girls, black hair, 1boy, brown eyes, jewelry, sitting, solo focus, day, midriff, indoors, necklace, mole, cup, lips, chair, table, realistic, coffee, cafe
|
img/100_Lena person/14.png
ADDED
|
Git LFS Details
|
img/100_Lena person/14.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, brown hair, navel, holding, brown eyes, medium breasts, sitting, closed mouth, nipples, small breasts, shorts, indoors, stomach, clothes lift, lips, short shorts, no bra, arm support, shirt lift, phone, cellphone, tank top, smartphone, holding phone, realistic, nose, selfie, camouflage, barcode
|
img/100_Lena person/15.png
ADDED
|
Git LFS Details
|
img/100_Lena person/15.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1girl, solo, long hair, looking at viewer, smile, simple background, brown hair, black hair, green eyes, parted lips, teeth, lips, eyelashes, portrait, close-up, freckles, realistic, nose
|
img/100_Lena person/2.png
ADDED
|
Git LFS Details
|
img/100_Lena person/2.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, smile, brown hair, navel, holding, cleavage, brown eyes, medium breasts, sitting, closed mouth, underwear, collarbone, outdoors, day, water, bra, tree, lips, phone, cellphone, nature, smartphone, reflection, holding phone, sports bra, realistic, selfie, river, lake
|
img/100_Lena person/3.png
ADDED
|
Git LFS Details
|
img/100_Lena person/3.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
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| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, smile, brown hair, navel, brown eyes, underwear, panties, indoors, bra, mole, flat chest, covered nipples, lips, pillow, bed, on bed, sports bra, realistic, dirty
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img/100_Lena person/4.png
ADDED
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Git LFS Details
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img/100_Lena person/4.txt
ADDED
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@@ -0,0 +1 @@
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| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, smile, brown hair, navel, holding, brown eyes, sitting, closed mouth, underwear, panties, small breasts, indoors, bra, lips, phone, cellphone, smartphone, holding phone, sports bra, realistic, nose, selfie, brand name imitation, grey panties
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img/100_Lena person/5.png
ADDED
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Git LFS Details
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img/100_Lena person/5.txt
ADDED
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@@ -0,0 +1 @@
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| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, brown hair, holding, brown eyes, sitting, closed mouth, collarbone, small breasts, indoors, bra, mole, flat chest, covered nipples, lips, bed, phone, cellphone, smartphone, holding phone, sports bra, sportswear, realistic, nose, selfie, blue bra
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img/100_Lena person/6.png
ADDED
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Git LFS Details
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img/100_Lena person/6.txt
ADDED
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@@ -0,0 +1 @@
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| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, brown hair, black hair, navel, brown eyes, sitting, underwear, collarbone, panties, small breasts, indoors, bra, flat chest, covered nipples, lips, pillow, bed, piercing, thick eyebrows, blue panties, sports bra, realistic, nose, lamp, blue bra, navel piercing, aqua panties
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img/100_Lena person/7.png
ADDED
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Git LFS Details
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img/100_Lena person/7.txt
ADDED
|
@@ -0,0 +1 @@
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| 1 |
+
1girl, solo, long hair, breasts, looking at viewer, smile, brown hair, black hair, navel, holding, brown eyes, underwear, panties, small breasts, indoors, bra, white panties, covered nipples, lips, phone, underwear only, cellphone, smartphone, white bra, holding phone, sports bra, realistic, nose, selfie
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