Datasets:
kratosboy507
/
kratos_configs

Dataset card Data Studio Files Community
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 38 new columns ({'dora_wd', 'unit', 'use_tucker', 'block_alphas', 'train_norm', 'dim_from_weights', 'constrain', 'module_dropout', 'network_alpha', 'training_comment', 'scale_weight_norms', 'stop_text_encoder_training_pct', 'rescaled', 'down_lr_weight', 'train_on_input', 'decompose_both', 'LoRA_type', 'network_dropout', 'LyCORIS_preset', 'conv_dim', 'block_dims', 'network_dim', 'text_encoder_lr', 'use_cp', 'conv_block_alphas', 'block_lr_zero_threshold', 'rank_dropout_scale', 'unet_lr', 'mid_lr_weight', 'conv_block_dims', 'max_grad_norm', 'up_lr_weight', 'use_scalar', 'bypass_mode', 'network_weights', 'factor', 'rank_dropout', 'conv_alpha'}) and 51 missing columns ({'sd3_cache_text_encoder_outputs', 'logit_std', 'save_last_n_epochs', 'sd3_text_encoder_batch_size', 'weighting_scheme', 'learning_rate_te1', 'no_token_padding', 'discrete_flow_shift', 'cpu_offload_checkpointing', 'log_config', 'timestep_sampling', 'flux1_t5xxl', 'skip_cache_check', 'fused_backward_pass', 'fused_optimizer_groups', 'mem_eff_save', 'clip_l', 'lr_scheduler_type', 'save_t5xxl', 'model_prediction_type', 'blocks_to_swap', 'sd3_cache_text_encoder_outputs_to_disk', 'flux1_clip_l', 'flux1_cache_text_encoder_outputs_to_disk', 'flux_fused_backward_pass', 'ae', 'learning_rate_te', 'logit_mean', 'disable_mmap_load_safetensors', 'mode_scale', 'apply_t5_attn_mask', 'flux1_checkbox', 'blockwise_fused_optimizers', 'single_blocks_to_swap', 'split_mode', 'save_clip', 't5xxl_device', 'clip_g', 'save_last_n_epochs_state', 'flux1_cache_text_encoder_outputs', 'save_as_bool', 'stop_text_encoder_training', 'learning_rate_te2', 'double_blocks_to_swap', 't5xxl_dtype', 't5xxl', 't5xxl_max_token_length', 'train_blocks', 'guidance_scale', 'sd3_checkbox', 'lr_warmup_steps'}).

This happened while the json dataset builder was generating data using

hf://datasets/kratosboy507/kratos_configs/senajuo2idol_noobv75_20241209-003658.json (at revision c8e8663bd8a4d74931fd0031d515da7ca06e6f51)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              LoRA_type: string
              LyCORIS_preset: string
              adaptive_noise_scale: int64
              additional_parameters: string
              async_upload: bool
              block_alphas: string
              block_dims: string
              block_lr_zero_threshold: string
              bucket_no_upscale: bool
              bucket_reso_steps: int64
              bypass_mode: bool
              cache_latents: bool
              cache_latents_to_disk: bool
              caption_dropout_every_n_epochs: int64
              caption_dropout_rate: int64
              caption_extension: string
              clip_skip: int64
              color_aug: bool
              constrain: int64
              conv_alpha: int64
              conv_block_alphas: string
              conv_block_dims: string
              conv_dim: int64
              dataset_config: string
              debiased_estimation_loss: bool
              decompose_both: bool
              dim_from_weights: bool
              dora_wd: bool
              down_lr_weight: string
              dynamo_backend: string
              dynamo_mode: string
              dynamo_use_dynamic: bool
              dynamo_use_fullgraph: bool
              enable_bucket: bool
              epoch: int64
              extra_accelerate_launch_args: string
              factor: int64
              flip_aug: bool
              fp8_base: bool
              full_bf16: bool
              full_fp16: bool
              gpu_ids: string
              gradient_accumulation_steps: int64
              gradient_checkpointing: bool
              huber_c: int64
              huber_schedule: string
              huggingface_path_in_repo: string
              huggingface_repo_id: string
              huggingface_repo_type: string
              huggingface_repo_visibility: string
              huggingface_token: string
              ip_noise_gamma: int64
              ip_noise_gamma_random_strength: bool
              keep_tokens: int64
              learning_rate: int64
              log_tracker_config: string
              log_tracker_name: string
              log_with: string
              logging_dir: string
              loss_type: string
              lr_scheduler: string
              lr_scheduler_args: string
              lr_scheduler_num_cycles: int64
              lr_scheduler_power: int64
              lr_warmup: i
              ...
              etwork_dim: int64
              network_dropout: int64
              network_weights: string
              noise_offset: double
              noise_offset_random_strength: bool
              noise_offset_type: string
              num_cpu_threads_per_process: int64
              num_machines: int64
              num_processes: int64
              optimizer: string
              optimizer_args: string
              output_dir: string
              output_name: string
              persistent_data_loader_workers: bool
              pretrained_model_name_or_path: string
              prior_loss_weight: int64
              random_crop: bool
              rank_dropout: int64
              rank_dropout_scale: bool
              reg_data_dir: string
              rescaled: bool
              resume: string
              resume_from_huggingface: string
              sample_every_n_epochs: int64
              sample_every_n_steps: int64
              sample_prompts: string
              sample_sampler: string
              save_every_n_epochs: int64
              save_every_n_steps: int64
              save_last_n_steps: int64
              save_last_n_steps_state: int64
              save_model_as: string
              save_precision: string
              save_state: bool
              save_state_on_train_end: bool
              save_state_to_huggingface: bool
              scale_v_pred_loss_like_noise_pred: bool
              scale_weight_norms: int64
              sdxl: bool
              sdxl_cache_text_encoder_outputs: bool
              sdxl_no_half_vae: bool
              seed: int64
              shuffle_caption: bool
              stop_text_encoder_training_pct: int64
              text_encoder_lr: int64
              train_batch_size: int64
              train_data_dir: string
              train_norm: bool
              train_on_input: bool
              training_comment: string
              unet_lr: int64
              unit: int64
              up_lr_weight: string
              use_cp: bool
              use_scalar: bool
              use_tucker: bool
              v2: bool
              v_parameterization: bool
              v_pred_like_loss: int64
              vae: string
              vae_batch_size: int64
              wandb_api_key: string
              wandb_run_name: string
              weighted_captions: bool
              xformers: string
              to
              {'adaptive_noise_scale': Value(dtype='int64', id=None), 'additional_parameters': Value(dtype='string', id=None), 'ae': Value(dtype='string', id=None), 'apply_t5_attn_mask': Value(dtype='bool', id=None), 'async_upload': Value(dtype='bool', id=None), 'blocks_to_swap': Value(dtype='int64', id=None), 'blockwise_fused_optimizers': Value(dtype='bool', id=None), 'bucket_no_upscale': Value(dtype='bool', id=None), 'bucket_reso_steps': Value(dtype='int64', id=None), 'cache_latents': Value(dtype='bool', id=None), 'cache_latents_to_disk': Value(dtype='bool', id=None), 'caption_dropout_every_n_epochs': Value(dtype='int64', id=None), 'caption_dropout_rate': Value(dtype='int64', id=None), 'caption_extension': Value(dtype='string', id=None), 'clip_g': Value(dtype='string', id=None), 'clip_l': Value(dtype='string', id=None), 'clip_skip': Value(dtype='int64', id=None), 'color_aug': Value(dtype='bool', id=None), 'cpu_offload_checkpointing': Value(dtype='bool', id=None), 'dataset_config': Value(dtype='string', id=None), 'debiased_estimation_loss': Value(dtype='bool', id=None), 'disable_mmap_load_safetensors': Value(dtype='bool', id=None), 'discrete_flow_shift': Value(dtype='float64', id=None), 'double_blocks_to_swap': Value(dtype='int64', id=None), 'dynamo_backend': Value(dtype='string', id=None), 'dynamo_mode': Value(dtype='string', id=None), 'dynamo_use_dynamic': Value(dtype='bool', id=None), 'dynamo_use_fullgraph': Value(dtype='bool', id=None), 'enable_bucket': Value(dtype='bool', id=None), '
              ...
               'sd3_cache_text_encoder_outputs_to_disk': Value(dtype='bool', id=None), 'sd3_checkbox': Value(dtype='bool', id=None), 'sd3_text_encoder_batch_size': Value(dtype='int64', id=None), 'sdxl': Value(dtype='bool', id=None), 'sdxl_cache_text_encoder_outputs': Value(dtype='bool', id=None), 'sdxl_no_half_vae': Value(dtype='bool', id=None), 'seed': Value(dtype='int64', id=None), 'shuffle_caption': Value(dtype='bool', id=None), 'single_blocks_to_swap': Value(dtype='int64', id=None), 'skip_cache_check': Value(dtype='bool', id=None), 'split_mode': Value(dtype='bool', id=None), 'stop_text_encoder_training': Value(dtype='int64', id=None), 't5xxl': Value(dtype='string', id=None), 't5xxl_device': Value(dtype='string', id=None), 't5xxl_dtype': Value(dtype='string', id=None), 't5xxl_max_token_length': Value(dtype='int64', id=None), 'timestep_sampling': Value(dtype='string', id=None), 'train_batch_size': Value(dtype='int64', id=None), 'train_blocks': Value(dtype='string', id=None), 'train_data_dir': Value(dtype='string', id=None), 'v2': Value(dtype='bool', id=None), 'v_parameterization': Value(dtype='bool', id=None), 'v_pred_like_loss': Value(dtype='int64', id=None), 'vae': Value(dtype='string', id=None), 'vae_batch_size': Value(dtype='int64', id=None), 'wandb_api_key': Value(dtype='string', id=None), 'wandb_run_name': Value(dtype='string', id=None), 'weighted_captions': Value(dtype='bool', id=None), 'weighting_scheme': Value(dtype='string', id=None), 'xformers': Value(dtype='string', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 38 new columns ({'dora_wd', 'unit', 'use_tucker', 'block_alphas', 'train_norm', 'dim_from_weights', 'constrain', 'module_dropout', 'network_alpha', 'training_comment', 'scale_weight_norms', 'stop_text_encoder_training_pct', 'rescaled', 'down_lr_weight', 'train_on_input', 'decompose_both', 'LoRA_type', 'network_dropout', 'LyCORIS_preset', 'conv_dim', 'block_dims', 'network_dim', 'text_encoder_lr', 'use_cp', 'conv_block_alphas', 'block_lr_zero_threshold', 'rank_dropout_scale', 'unet_lr', 'mid_lr_weight', 'conv_block_dims', 'max_grad_norm', 'up_lr_weight', 'use_scalar', 'bypass_mode', 'network_weights', 'factor', 'rank_dropout', 'conv_alpha'}) and 51 missing columns ({'sd3_cache_text_encoder_outputs', 'logit_std', 'save_last_n_epochs', 'sd3_text_encoder_batch_size', 'weighting_scheme', 'learning_rate_te1', 'no_token_padding', 'discrete_flow_shift', 'cpu_offload_checkpointing', 'log_config', 'timestep_sampling', 'flux1_t5xxl', 'skip_cache_check', 'fused_backward_pass', 'fused_optimizer_groups', 'mem_eff_save', 'clip_l', 'lr_scheduler_type', 'save_t5xxl', 'model_prediction_type', 'blocks_to_swap', 'sd3_cache_text_encoder_outputs_to_disk', 'flux1_clip_l', 'flux1_cache_text_encoder_outputs_to_disk', 'flux_fused_backward_pass', 'ae', 'learning_rate_te', 'logit_mean', 'disable_mmap_load_safetensors', 'mode_scale', 'apply_t5_attn_mask', 'flux1_checkbox', 'blockwise_fused_optimizers', 'single_blocks_to_swap', 'split_mode', 'save_clip', 't5xxl_device', 'clip_g', 'save_last_n_epochs_state', 'flux1_cache_text_encoder_outputs', 'save_as_bool', 'stop_text_encoder_training', 'learning_rate_te2', 'double_blocks_to_swap', 't5xxl_dtype', 't5xxl', 't5xxl_max_token_length', 'train_blocks', 'guidance_scale', 'sd3_checkbox', 'lr_warmup_steps'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/kratosboy507/kratos_configs/senajuo2idol_noobv75_20241209-003658.json (at revision c8e8663bd8a4d74931fd0031d515da7ca06e6f51)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

adaptive_noise_scale
int64
additional_parameters
string
ae
string
apply_t5_attn_mask
bool
async_upload
bool
blocks_to_swap
int64
blockwise_fused_optimizers
bool
bucket_no_upscale
bool
bucket_reso_steps
int64
cache_latents
bool
cache_latents_to_disk
bool
caption_dropout_every_n_epochs
int64
caption_dropout_rate
int64
caption_extension
string
clip_g
string
clip_l
string
clip_skip
int64
color_aug
bool
cpu_offload_checkpointing
bool
dataset_config
string
debiased_estimation_loss
bool
disable_mmap_load_safetensors
bool
discrete_flow_shift
float64
double_blocks_to_swap
int64
dynamo_backend
string
dynamo_mode
string
dynamo_use_dynamic
bool
dynamo_use_fullgraph
bool
enable_bucket
bool
epoch
int64
extra_accelerate_launch_args
string
flip_aug
bool
flux1_cache_text_encoder_outputs
bool
flux1_cache_text_encoder_outputs_to_disk
bool
flux1_checkbox
bool
flux1_clip_l
string
flux1_t5xxl
string
flux_fused_backward_pass
bool
fp8_base
bool
full_bf16
bool
full_fp16
bool
fused_backward_pass
bool
fused_optimizer_groups
int64
gpu_ids
string
gradient_accumulation_steps
int64
gradient_checkpointing
bool
guidance_scale
int64
huber_c
float64
huber_schedule
string
huggingface_path_in_repo
string
huggingface_repo_id
string
huggingface_repo_type
string
huggingface_repo_visibility
string
huggingface_token
string
ip_noise_gamma
int64
ip_noise_gamma_random_strength
bool
keep_tokens
int64
learning_rate
float64
learning_rate_te
int64
learning_rate_te1
float64
learning_rate_te2
float64
log_config
bool
log_tracker_config
string
log_tracker_name
string
log_with
string
logging_dir
string
logit_mean
int64
logit_std
int64
loss_type
string
lr_scheduler
string
lr_scheduler_args
string
lr_scheduler_num_cycles
int64
lr_scheduler_power
int64
lr_scheduler_type
string
lr_warmup
int64
lr_warmup_steps
int64
main_process_port
int64
masked_loss
bool
max_bucket_reso
int64
max_data_loader_n_workers
int64
max_resolution
string
max_timestep
int64
max_token_length
int64
max_train_epochs
int64
max_train_steps
int64
mem_eff_attn
bool
mem_eff_save
bool
metadata_author
string
metadata_description
string
metadata_license
string
metadata_tags
string
metadata_title
string
min_bucket_reso
int64
min_snr_gamma
int64
min_timestep
int64
mixed_precision
string
mode_scale
float64
model_list
string
model_prediction_type
string
multi_gpu
bool
multires_noise_discount
float64
multires_noise_iterations
int64
no_token_padding
bool
noise_offset
float64
noise_offset_random_strength
bool
noise_offset_type
string
num_cpu_threads_per_process
int64
num_machines
int64
num_processes
int64
optimizer
string
optimizer_args
string
output_dir
string
output_name
string
persistent_data_loader_workers
bool
pretrained_model_name_or_path
string
prior_loss_weight
int64
random_crop
bool
reg_data_dir
string
resume
string
resume_from_huggingface
string
sample_every_n_epochs
int64
sample_every_n_steps
int64
sample_prompts
string
sample_sampler
string
save_as_bool
bool
save_clip
bool
save_every_n_epochs
int64
save_every_n_steps
int64
save_last_n_epochs
int64
save_last_n_epochs_state
int64
save_last_n_steps
int64
save_last_n_steps_state
int64
save_model_as
string
save_precision
string
save_state
bool
save_state_on_train_end
bool
save_state_to_huggingface
bool
save_t5xxl
bool
scale_v_pred_loss_like_noise_pred
bool
sd3_cache_text_encoder_outputs
bool
sd3_cache_text_encoder_outputs_to_disk
bool
sd3_checkbox
bool
sd3_text_encoder_batch_size
int64
sdxl
bool
sdxl_cache_text_encoder_outputs
bool
sdxl_no_half_vae
bool
seed
int64
shuffle_caption
bool
single_blocks_to_swap
int64
skip_cache_check
bool
split_mode
bool
stop_text_encoder_training
int64
t5xxl
string
t5xxl_device
string
t5xxl_dtype
string
t5xxl_max_token_length
int64
timestep_sampling
string
train_batch_size
int64
train_blocks
string
train_data_dir
string
v2
bool
v_parameterization
bool
v_pred_like_loss
int64
vae
string
vae_batch_size
int64
wandb_api_key
string
wandb_run_name
string
weighted_captions
bool
weighting_scheme
string
xformers
string
LoRA_type
string
LyCORIS_preset
string
block_alphas
string
block_dims
string
block_lr_zero_threshold
string
bypass_mode
bool
constrain
int64
conv_alpha
int64
conv_block_alphas
string
conv_block_dims
string
conv_dim
int64
decompose_both
bool
dim_from_weights
bool
dora_wd
bool
down_lr_weight
string
factor
int64
max_grad_norm
int64
mid_lr_weight
string
module_dropout
int64
network_alpha
int64
network_dim
int64
network_dropout
int64
network_weights
string
rank_dropout
int64
rank_dropout_scale
bool
rescaled
bool
scale_weight_norms
int64
stop_text_encoder_training_pct
int64
text_encoder_lr
int64
train_norm
bool
train_on_input
bool
training_comment
string
unet_lr
int64
unit
int64
up_lr_weight
string
use_cp
bool
use_scalar
bool
use_tucker
bool
0
/home/Ubuntu/Downloads/ae.safetensors
false
false
0
false
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64
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0
.txt
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3.1582
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no
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false
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200
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/home/Ubuntu/Downloads/clip_l.safetensors
/home/Ubuntu/Downloads/t5xxl_fp16.safetensors
true
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0
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0.000004
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0.00001
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l2
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1
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2,048
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1024,1024
1,000
75
0
0
false
true
256
0
0
bf16
1.29
custom
raw
false
0.3
0
false
0
false
Original
2
1
1
Adafactor
scale_parameter=False relative_step=False warmup_init=False weight_decay=0.01
/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models
Quality_1
false
/home/Ubuntu/Downloads/flux1-dev.safetensors
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euler_a
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safetensors
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bf16
512
sigmoid
1
all
/home/Ubuntu/Downloads/training_imgs
false
false
0
4
false
logit_normal
xformers
null
null
null
null
null
null
null
null
null
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/home/Ubuntu/Downloads/clip_l.safetensors
/home/Ubuntu/Downloads/t5xxl_fp16.safetensors
true
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0
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1
true
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Original
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