Trained on Anima Preview-3-base Assume that any lora trained on the preview version won't work well on the final version. Recommended prompt structure: Positive prompt (quality tags at the start of prompt): masterpiece, best quality, very aesthetic, {{tags}}, {{natural language}} Updated dataset of 386 images, all masterpiece tagged images trained in Kirazuri (Anima) model version 2 dataset. Trained at 1024 x 1024, 1280 x 1280, and 1536 x 1024 resolutions. Previews are mostly generated at 1536 x 1024 or 1024 x 1536. diffusion-pipe commit b0aa4f1e03169f3280c8518d37570a448420f8be # dataset-anima.toml resolutions = [1024, 1280, 1536] enable_ar_bucket = true min_ar = 0.5 max_ar = 2.0 num_ar_buckets = 9 # Totals # 386 images # 15504 samples/epoch # 153 images # 48 samples/image - 7344 samples/epoch [[directory]] path = '/mnt/d/training_data/0_masterpieces_kirazuri/1536x1536' repeats = 16 resolutions = [1024, 1280, 1536] # 44 images # 48 samples/image - 2112 samples/epoch [[directory]] path = '/mnt/d/training_data/0_masterpieces_kirazuri/1280x1280' repeats = 24 resolutions = [1024, 1280] # 189 images # 32 samples/image - 6048 samples/epoch [[directory]] path = '/mnt/d/training_data/0_masterpieces_kirazuri/1024x1024' repeats = 32 resolutions = [1024] # anima-lora.toml output_dir = '/mnt/d/anima/training_output/masterpieces-v5' dataset = 'dataset-anima.toml' # training settings epochs = 5 # Per-resolution batch sizes micro_batch_size_per_gpu = [[1024, 32], [1280, 24], [1536, 16]] pipeline_stages = 1 gradient_accumulation_steps = 1 gradient_clipping = 1 warmup_steps = 100 lr_scheduler = 'cosine' # 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/models/diffusion_models/anima-preview3-base.safetensors' vae_path = '/mnt/c/workspace/models/vae/qwen_image_vae.safetensors' llm_path = '/mnt/c/workspace/models/text_encoders/qwen_3_06b_base.safetensors' dtype = 'bfloat16' #cache_text_embeddings = false llm_adapter_lr = 1e-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