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SD3.5-Large-Queso-toolkit2

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sd3.5-large
lora
replicate
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SD3.5-Large-Queso-toolkit2
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job: custom_job
config:
  name: sd3.5l_train_replicate
  process:
  - type: custom_sd_trainer
    training_folder: output
    device: cuda:0
    trigger_word: QSO
    network:
      type: lora
      linear: 16
      linear_alpha: 16
    save:
      dtype: float16
      save_every: 701
      max_step_saves_to_keep: 1
    datasets:
    - folder_path: input_images
      caption_ext: txt
      caption_dropout_rate: 0.05
      shuffle_tokens: false
      cache_latents_to_disk: false
      cache_latents: true
      resolution:
      - 512
      - 768
      - 1024
    train:
      batch_size: 1
      steps: 700
      gradient_accumulation_steps: 1
      train_unet: true
      train_text_encoder: false
      content_or_style: balanced
      gradient_checkpointing: true
      noise_scheduler: flowmatch
      optimizer: adamw8bit
      lr: 0.0004
      ema_config:
        use_ema: true
        ema_decay: 0.99
      dtype: bf16
    model:
      name_or_path: stable-diffusion-3.5-large
      is_v3: true
      quantize: true
    sample:
      sampler: flowmatch
      sample_every: 701
      width: 1024
      height: 1024
      prompts: []
      neg: ''
      seed: 42
      walk_seed: true
      guidance_scale: 3.5
      sample_steps: 28
meta:
  name: sd3.5l_train_replicate
  version: '1.0'