<h2 id="arknights:-endfield-or-operators-collection">Arknights: Endfield | Operators Collection</h2>Intended to generate non-commercial fan works of Operators from the Arknights: Endfield video game.ℹ️ LoRA work best when applied to the base models on which they are trained. Please read the About This Version on the appropriate base models and workflow/training information.Trained on a large mixed NL and tags dataset with 30% tag dropout rate, at mixed [1024, 1280] resolutions. Previews are mostly generated at 1024x1536.Operators (game version 1.0):<pre><code>
female endministrator \(arknights\)
male endministrator \(arknights\)
perlica \(arknights\)
chen qianyu \(arknights\)

akekuri \(arknights\)
alesh \(arknights\)
antal \(arknights\)
arclight \(arknights\)
ardelia \(arknights\)
avywenna \(arknights\)
catcher \(arknights\)
da pan \(arknights\)
estella \(arknights\)
fluorite \(arknights\)
gilberta \(arknights\)
laevatain \(arknights\)
last rite \(arknights\)
lifeng \(arknights\)
snowshine \(arknights\)
wulfgard \(arknights\)
xaihi \(arknights\)
yvonne \(arknights\)
</code></pre>Operators (game version 1.1):<pre><code>
mi fu \(arknights\)
rossi \(arknights\)
tangtang \(arknights\)
zhuang fangyi \(arknights\)
</code></pre>Antagonists:<pre><code>
ardashir \(arknights\)
nefarith \(arknights\)
</code></pre>Works best in combination with NL if you name a character, then describe their basic appearance.<pre><code>
A vibrant and dynamic illustration of Yvonne from Arknights: Endfield, featuring her with long pink hair styled in twintails, pointy ears, and small horns, along with a playful tail...
</code></pre>To be fixed:<code>Pogranichnik</code> had a mistake for his labelling<code>Ember</code> did not seem to learn her outfit/features

Arknights: Endfield | Operators Collection

Trained on <a target="_blank" rel="ugc" href="https://civitai.com/models/2458426/anima-official?modelVersionId=2836417">Anima Preview 3 Base</a>Dataset uses a mix of tags and natural language captionsLess prominent characters were not learned as well in this versionTraining config:<pre><code># trained using diffusion-pipe commit 6e95020cad0b3cd7dcb93ce42b358669051bf6d2

output_dir = '/mnt/d/anima/training_output/arknights3'

dataset = 'dataset-anima.toml'

# training settings
epochs = 1000
# Per-resolution batch sizes
micro_batch_size_per_gpu = [[512, 64], [1024, 32], [1536, 16]]
pipeline_stages = 1
gradient_accumulation_steps = 1
gradient_clipping = 1
warmup_steps = 100

# misc settings
save_every_n_epochs = 1
#save_every_n_steps = 1000
#save_every_n_examples = 4096000
#checkpoint_every_n_epochs = 1
#checkpoint_every_n_minutes = 120
activation_checkpointing = true
#reentrant_activation_checkpointing = true

partition_method = 'parameters'
# partition_method = 'manual'
# partition_split = [10]

save_dtype = 'bfloat16'
caching_batch_size = 1
map_num_proc = 8
steps_per_print = 1
compile = true

[model]
type = 'anima'
transformer_path = '/mnt/c/workspace/ComfyUI_windows_portable_nvidia/ComfyUI_windows_portable/ComfyUI/models/diffusion_models/anima-preview3-base.safetensors'
vae_path = '/mnt/c/workspace/ComfyUI_windows_portable_nvidia/ComfyUI_windows_portable/ComfyUI/models/vae/qwen_image_vae.safetensors'
llm_path = '/mnt/c/workspace/ComfyUI_windows_portable_nvidia/ComfyUI_windows_portable/ComfyUI/models/text_encoders/qwen_3_06b_base.safetensors'
dtype = 'bfloat16'
#cache_text_embeddings = false
llm_adapter_lr = 2e-6
#timestep_sample_method = 'uniform'
#flux_shift = true
#multiscale_loss_weight = 0.5
sigmoid_scale = 1.3

[adapter]
type = 'lora'
rank = 32
dtype = 'bfloat16'

[optimizer]
type = 'adamw_optimi'
lr = 4e-5
betas = [0.9, 0.99]
weight_decay = 0.01
eps = 1e-8</code></pre>Dataset config:<pre><code>resolutions = [512, 1024, 1536]

enable_ar_bucket = true
min_ar = 0.5
max_ar = 2.0
num_ar_buckets = 9

[[directory]]
path = '/mnt/d/training_data/images_arknights_captions'
repeats = 4</code></pre>

Files with SHA256: 4a250ef7c525a9d03b6897c97c7fc301013dc675def3e25ac32fd8e6fe223e0c