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Reviews
(36)
Published
Oct 6, 2025
Base Model
Wan Video 2.2 T2V-A14B
Training
Steps: 5,600
Epochs: 70
Usage Tips
Strength: 1
Hash
AutoV2
B7F6303A67
Trigger Words
OIIA_cat
dataset.toml
resolutions = [ [ 192, 342,], [ 480, 854,],]
enable_ar_bucket = true
min_ar = 0.5
max_ar = 2.0
num_ar_buckets = 7
frame_buckets = [ 1, 48, 51, 72, 75, 80, 81,]
[[directory]]
path = "/home/user/oiia_cat_videos_16fps"
num_repeats = 4train.toml
output_dir = "/home/user/oiia_cat_A14B/A14B"
dataset = "/home/user/dataset_A14B.toml"
epochs = 200
micro_batch_size_per_gpu = 1
pipeline_stages = 1
gradient_accumulation_steps = 1
gradient_clipping = 1
warmup_steps = 10
eval_every_n_epochs = 1
eval_before_first_step = true
eval_micro_batch_size_per_gpu = 1
eval_gradient_accumulation_steps = 1
save_every_n_epochs = 10
activation_checkpointing = true
partition_method = "parameters"
save_dtype = "bfloat16"
caching_batch_size = 1
steps_per_print = 10
video_clip_mode = "single_beginning"
blocks_to_swap = 32
[model]
type = "wan"
ckpt_path = "/home/user/Wan2.2-T2V-A14B"
dtype = "bfloat16"
transformer_dtype = "float8"
timestep_sample_method = "logit_normal"
transformer_path = "/home/user/Wan2.2-T2V-A14B/low_noise_model"
min_t = 0
max_t = 0.875
[adapter]
type = "lora"
rank = 32
dtype = "bfloat16"
[optimizer]
type = "adamw_optimi"
lr = 5e-5
betas = [ 0.9, 0.99,]
weight_decay = 0.01
eps = 1e-8Show more

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5850 1 2 3 4 5 6 7 8 90 1 2 3 4 5 6 7 8 90 1 2 3 4 5 6 7 8 9
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The [object] froze for a few seconds, and then abruptly began to spin in place.You can find detailed information about the versions in these articles:
