Got this one working finally. Will use my profile as a place to take notes on my own training settings and dataset iterations Notes:Manually resized all imagesReduced image batch from 300+ to 32 No captioning or tags (Better for styles)Added "ABARA" trigger wordABARA Lora dataset <a target="_blank" rel="ugc" href="https://drive.google.com/drive/folders/1EwOoWwQfycye9w4gehE8wViY4TryLR4g?usp=sharing">https://drive.google.com/drive/folders/1EwOoWwQfycye9w4gehE8wViY4TryLR4g?usp=sharing</a> CONFIG: Using Ostris AI Toolkit<pre><code>---
job: "extension"
config:
 name: "abara-v2"
 process:
 - type: "diffusion_trainer"
 training_folder: "C:\\Ostris-AI-Toolkit\\AI-Toolkit\\output"
 sqlite_db_path: "./aitk_db.db"
 device: "cuda"
 trigger_word: "abara"
 performance_log_every: 10
 network:
 type: "lora"
 linear: 128
 linear_alpha: 128
 conv: 128
 conv_alpha: 128
 lokr_full_rank: true
 lokr_factor: -1
 network_kwargs:
 ignore_if_contains: []
 save:
 dtype: "bf16"
 save_every: 600
 max_step_saves_to_keep: 16
 save_format: "diffusers"
 push_to_hub: false
 datasets:
 - folder_path: "C:\\Ostris-AI-Toolkit\\AI-Toolkit\\datasets/abara_ready"
 mask_path: null
 mask_min_value: 0.1
 default_caption: ""
 caption_ext: "txt"
 caption_dropout_rate: 0
 cache_latents_to_disk: true
 is_reg: false
 network_weight: 1
 resolution:
 - 1536
 controls: []
 shrink_video_to_frames: true
 num_frames: 1
 do_i2v: true
 flip_x: false
 flip_y: false
 train:
 batch_size: 1
 bypass_guidance_embedding: false
 steps: 6000
 gradient_accumulation: 1
 train_unet: true
 train_text_encoder: false
 gradient_checkpointing: true
 noise_scheduler: "flowmatch"
 optimizer: "adamw8bit"
 timestep_type: "weighted"
 content_or_style: "balanced"
 optimizer_params:
 weight_decay: 0.0001
 unload_text_encoder: false
 cache_text_embeddings: true
 lr: 0.0001
 ema_config:
 use_ema: false
 ema_decay: 0.99
 skip_first_sample: true
 force_first_sample: false
 disable_sampling: false
 dtype: "bf16"
 diff_output_preservation: false
 diff_output_preservation_multiplier: 1
 diff_output_preservation_class: "person"
 switch_boundary_every: 1
 loss_type: "mse"
 model:
 name_or_path: "Tongyi-MAI/Z-Image-Turbo"
 quantize: false
 qtype: "qfloat8"
 quantize_te: false
 qtype_te: "qfloat8"
 arch: "zimage:turbo"
 low_vram: true
 model_kwargs: {}
 layer_offloading: false
 layer_offloading_text_encoder_percent: 1
 layer_offloading_transformer_percent: 1
 assistant_lora_path: "ostris/zimage_turbo_training_adapter/zimage_turbo_training_adapter_v2.safetensors"
 sample:
 sampler: "flowmatch"
 sample_every: 250000
 width: 1536
 height: 1536
 samples:
 - prompt: "man with red hair, playing chess at the park, bomb going off in the background"
 - prompt: "a man holding a coffee cup, in a beanie, sitting at a cafe"
 - prompt: "a horse is a DJ at a night club, fish eye lens, smoke machine, lazer lights, holding a martini"
 - prompt: "a man showing off his cool new t shirt at the beach, a shark is jumping out of the water in the background"
 - prompt: "a bear building a log cabin in the snow covered mountains"
 - prompt: "man playing the guitar, on stage, singing a song, laser lights, punk rocker"
 - prompt: "hipster man with a beard, building a chair, in a wood shop"
 - prompt: "photo of a man, white background, medium shot, modeling clothing, studio lighting, white backdrop"
 - prompt: "a man holding a sign that says, 'this is a sign'"
 - prompt: "a bulldog, in a post apocalyptic world, with a shotgun, in a leather jacket, in a desert, with a motorcycle"
 neg: ""
 seed: 42
 walk_seed: true
 guidance_scale: 1
 sample_steps: 8
 num_frames: 1
 fps: 1
meta:
 name: "[name]"
 version: "1.0"
</code></pre>

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