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Upload train_config.toml with huggingface_hub

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+ # Training config for Anima Preview 2 (RECOMENDADO)
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+ # Project: loven_base_init
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+ # Generated: 2026-04-03 04:45:11
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+ # Edit this file before launching training!
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+
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+ # === Model ===
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+ pretrained_model_name_or_path = "/workspace/models/anima-preview2/split_files/diffusion_models/anima-preview2.safetensors"
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+ qwen3 = "/workspace/models/anima-preview2/split_files/text_encoders/qwen_3_06b_base.safetensors"
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+ vae = "/workspace/models/anima-preview2/split_files/vae/qwen_image_vae.safetensors"
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+ vae_chunk_size = 64
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+ vae_disable_cache = true
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+ # llm_adapter_lr = 0 # uncomment for full fine-tune only
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+ dataset_config = "/workspace/projects/loven_base_init/dataset.toml"
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+
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+ # === Network (LoRA) ===
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+ network_module = "networks.lora_anima"
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+ network_dim = 32
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+ network_alpha = 16
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+ network_train_unet_only = true
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+
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+ # === Attention ===
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+ attn_mode = "torch"
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+
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+ # === Precision & Memory ===
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+ mixed_precision = "bf16"
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+ # full_bf16 = true # uncomment if PyTorch >= 2.5 (saves VRAM, risk of NaN on older versions)
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+ gradient_checkpointing = true
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+
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+ # === Cache ===
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+ cache_latents = true
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+ cache_text_encoder_outputs = true
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+
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+ # === Timestep ===
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+ timestep_sampling = "sigmoid"
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+ weighting_scheme = "uniform"
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+ discrete_flow_shift = 3.0
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+ sigmoid_scale = 1.0
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+ # DO NOT set noise_offset — causes green tint artifacts on ANIMA
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+ # To use shift-based timestep: change timestep_sampling to 'shift'
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+
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+ # === Optimizer ===
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+ optimizer_type = "AdamW8bit"
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+ learning_rate = 2e-05
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+ lr_scheduler = "cosine"
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+ gradient_accumulation_steps = 1
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+ max_grad_norm = 1.0
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+ lr_warmup_steps = 0.1
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+
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+ # === Duration ===
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+ max_train_steps = 3000
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+
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+ # === Save ===
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+ save_every_n_steps = 250
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+ output_dir = "/workspace/projects/loven_base_init/outputs/20260403_044418"
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+ output_name = "loven_base_init"
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+ save_model_as = "safetensors"
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+ save_precision = "bf16"
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+
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+ # === Sampling ===
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+ sample_prompts = "/workspace/projects/loven_base_init/sample_prompts.txt"
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+ sample_every_n_steps = 100
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+
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+ # === Dataloader ===
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+ max_data_loader_n_workers = 2
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+ persistent_data_loader_workers = true
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+ seed = 42