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limitedpalette.txt

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+- target: "color" # what word for erasing the positive concept from
+  positive: "multicolored , polychromatic" # word to take the difference from the positive concept
+  unconditional: "limited palette color" # word to take the difference from the positive concept
+  neutral: "color" # starting point for conditioning the target
+  action: "erase" # erase or enhance
+  guidance_scale: 12
+  resolution: 512
+  dynamic_resolution: false
+  batch_size: 1 
+
+
+# - target: "" # what word for erasing the positive concept from
+#   positive: "a group of people"  # concept to erase
+#   unconditional: "a person" # word to take the difference from the positive concept
+#   neutral: "" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "" # what word for erasing the positive concept from
+#   positive: "high detail, 8k, intricate, detailed, high resolution, high res, high quality"  # concept to erase
+#   unconditional: "blurry, boring, fuzzy, low detail, low resolution, low res, low quality" # word to take the difference from the positive concept
+#   neutral: "" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "" # what word for erasing the positive concept from
+#   positive: "blurred background, narrow DOF, bokeh effect"  # concept to erase
+# #   unconditional: "high detail background, 8k, intricate, detailed, high resolution background, high res, high quality background" # word to take the difference from the positive concept
+#   unconditional: ""
+#   neutral: "" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "food" # what word for erasing the positive concept from
+#   positive: "food, expensive and fine dining" # concept to erase
+#   unconditional: "food, cheap and low quality" # word to take the difference from the positive concept
+#   neutral: "food" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "room" # what word for erasing the positive concept from
+#   positive: "room, dirty disorganised and cluttered" # concept to erase
+#   unconditional: "room, neat organised and clean" # word to take the difference from the positive concept
+#   neutral: "room" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "male person" # what word for erasing the positive concept from
+#   positive: "male person, with a surprised look" # concept to erase
+#   unconditional: "male person, with a disinterested look" # word to take the difference from the positive concept
+#   neutral: "male person" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "female person" # what word for erasing the positive concept from
+#   positive: "female person, with a surprised look" # concept to erase
+#   unconditional: "female person, with a disinterested look" # word to take the difference from the positive concept
+#   neutral: "female person" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "sky" # what word for erasing the positive concept from
+#   positive: "peaceful sky" # concept to erase
+#   unconditional: "sky" # word to take the difference from the positive concept
+#   neutral: "sky" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "sky" # what word for erasing the positive concept from
+#   positive: "chaotic dark sky" # concept to erase
+#   unconditional: "sky" # word to take the difference from the positive concept
+#   neutral: "sky" # starting point for conditioning the target
+#   action: "erase" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "person" # what word for erasing the positive concept from
+#   positive: "person, dull and desaturated, monochrome, rough and sloppy, lack of depth, flat and two-dimensional, stiff and lifeless, thick outlines" # concept to erase
+#   unconditional: "person" # word to take the difference from the positive concept
+#   neutral: "person" # starting point for conditioning the target
+#   action: "erase" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# overweight
+# - target: "art" # what word for erasing the positive concept from
+#   positive: "realistic art" # concept to erase
+#   unconditional: "art" # word to take the difference from the positive concept
+#   neutral: "art" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "art" # what word for erasing the positive concept from
+#   positive: "abstract art" # concept to erase
+#   unconditional: "art" # word to take the difference from the positive concept
+#   neutral: "art" # starting point for conditioning the target
+#   action: "erase" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# sky
+# - target: "weather" # what word for erasing the positive concept from
+#   positive: "bright pleasant weather" # concept to erase
+#   unconditional: "weather" # word to take the difference from the positive concept
+#   neutral: "weather" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "weather" # what word for erasing the positive concept from
+#   positive: "dark gloomy weather" # concept to erase
+#   unconditional: "weather" # word to take the difference from the positive concept
+#   neutral: "weather" # starting point for conditioning the target
+#   action: "erase" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# hair
+# - target: "person" # what word for erasing the positive concept from
+#   positive: "person with long hair" # concept to erase
+#   unconditional: "person" # word to take the difference from the positive concept
+#   neutral: "person" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "person" # what word for erasing the positive concept from
+#   positive: "person with short hair" # concept to erase
+#   unconditional: "person" # word to take the difference from the positive concept
+#   neutral: "person" # starting point for conditioning the target
+#   action: "erase" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1 
+# - target: "girl" # what word for erasing the positive concept from
+#   positive: "baby girl" # concept to erase
+#   unconditional: "girl" # word to take the difference from the positive concept
+#   neutral: "girl" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: -4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "boy" # what word for erasing the positive concept from
+#   positive: "old man" # concept to erase
+#   unconditional: "boy" # word to take the difference from the positive concept
+#   neutral: "boy" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: 4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1
+# - target: "boy" # what word for erasing the positive concept from
+#   positive: "baby boy" # concept to erase
+#   unconditional: "boy" # word to take the difference from the positive concept
+#   neutral: "boy" # starting point for conditioning the target
+#   action: "enhance" # erase or enhance
+#   guidance_scale: -4
+#   resolution: 512
+#   dynamic_resolution: false
+#   batch_size: 1

limitedpalette.yaml

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+prompts_file: "./examples/limitedpalette.txt"
+
+pretrained_model:
+  name_or_path: "I:/models/Stable-diffusion/V1.5/v1-5-pruned.safetensors" # you can also use .ckpt or .safetensors models
+  v2:  false # true if model is v2.x
+  v_pred: false # true if model uses v-prediction
+
+network:
+  type: "c3lier" # or "c3lier"
+  rank: 8
+  alpha: 4
+  training_method: "full" # selfattn, xattn, noxattn, or innoxattn
+
+train:
+  precision: "bfloat16"
+  noise_scheduler: "ddim" # or "ddpm", "lms", "euler_a"
+  iterations: 250
+  lr: 4e-4
+  optimizer: "AdamW"
+  lr_scheduler: "constant"
+  max_denoising_steps: 50
+
+save:
+  name: "limitedpalette"
+  path: "./LECO_output/limitedpalette"
+  per_steps: 250
+  precision: "bfloat16"
+
+logging:
+  use_wandb: false
+  verbose: false
+
+other:
+  use_xformers: true