Bernard Maltais commited on
Commit ·
2002a4d
1
Parent(s): c7bc6d2
1st commit
Browse files- README.md +38 -0
- aesthetic_embeddings/silvery_trait.pt +3 -0
- kohya_train_db_v9.ps1 +52 -0
- prompt_words.md +443 -0
- silvery_trait_v3.ckpt +3 -0
README.md
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---
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license: unknown
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---
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# Silvery Trait finetuned style Model
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Produced from publicly available pictures in landscape, portrait and square format.
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Using words found in `prompt_words.md` within your prompt will produce better results. Other words can be used also but will tend to produce "weaker" results. Combining the use of the Aesthetic Gradient file provided in the `easthetic_embeddings` folder can greatly enhance the results.
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## Model info
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The models included was trained on "multi-resolution" images.
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## Using the model
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* common subject prompt tokens: `<wathever>, by asd artstyle`
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## Example prompts
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`a sheep, symmetry, by asd artstyle`:
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* without easthetic_embeddings
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<img src="https://huggingface.co/cyburn/silvery_trait/resolve/main/1.png" alt="Picture." width="500"/>
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* with easthetic_embeddings
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<img src="https://huggingface.co/cyburn/silvery_trait/resolve/main/2.png" alt="Picture." width="500"/>
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`crow, skull, symmetry, flower, feather, circle, by asd artstyle`
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* without easthetic_embeddings
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<img src="https://huggingface.co/cyburn/silvery_trait/resolve/main/3.png" alt="Picture." width="500"/>
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* with easthetic_embeddings
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<img src="https://huggingface.co/cyburn/silvery_trait/resolve/main/4.png" alt="Picture." width="500"/>
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aesthetic_embeddings/silvery_trait.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:070550d3462c89b59ca0a93fb387a9b0bc8dd7ba157e87416957acd145e6879c
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size 3819
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kohya_train_db_v9.ps1
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# This powershell script will create a model using the fine tuning dreambooth method. It will require landscape,
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# portrait and square images.
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#
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# Adjust the script to your own needs
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# variable values
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$pretrained_model_name_or_path = "D:\models\v1-5-pruned-mse-vae.ckpt"
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$data_dir = "D:\dreambooth\silvery_trait\raw_data\all-images-v3"
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$train_dir = "D:\dreambooth\silvery_trait\"
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$resolution = "768,576"
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$logging_dir = "D:\dreambooth\silvery_trait\training_logs"
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$image_num = Get-ChildItem $data_dir -Recurse -File -Include *.png, *.jpg, *.webp | Measure-Object | %{$_.Count}
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Write-Output "image_num: $image_num"
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$learning_rate = 1e-6
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$dataset_repeats = 40
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$train_batch_size = 6
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$epoch = 4
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$save_every_n_epochs=1
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$mixed_precision="fp16"
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$num_cpu_threads_per_process=6
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# You should not have to change values past this point
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$output_dir = $train_dir + "\finetuned_model"
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$repeats = $image_num * $dataset_repeats
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$mts = [Math]::Ceiling($repeats / $train_batch_size * $epoch)
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Write-Output "Repeats: $repeats"
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.\venv\Scripts\activate
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accelerate launch --num_cpu_threads_per_process $num_cpu_threads_per_process train_db_fixed.py `
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--pretrained_model_name_or_path=$pretrained_model_name_or_path `
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--train_data_dir=$data_dir `
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--output_dir=$output_dir `
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--resolution=$resolution `
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--train_batch_size=$train_batch_size `
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--learning_rate=$learning_rate `
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--max_train_steps=$mts `
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--use_8bit_adam `
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--xformers `
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--mixed_precision=$mixed_precision `
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--cache_latents `
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--save_every_n_epochs=$save_every_n_epochs `
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--fine_tuning `
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--enable_bucket `
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--dataset_repeats=$dataset_repeats `
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--logging_dir=$logging_dir `
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--save_precision="fp16"
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prompt_words.md
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| 1 |
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# Prompt Words
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| 2 |
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List of prompt words known to the model
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| 4 |
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## Sorted by frequency
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| 6 |
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```txt
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Count Name
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----- ----
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87 a
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85 symmetry
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17 leaves
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15 two
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13 tree
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13 moon
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13 circle
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13 with
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13 an
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12 cloud
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12 and
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11 landscape
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10 coin
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10 water
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10 bird
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9 antler
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9 holding
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9 on
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9 the
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7 mountain
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7 sun
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6 art
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6 in
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6 deer
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6 concept
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6 wings
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5 stick
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5 bug
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5 horn
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5 feather
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5 star
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4 rabbit
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4 three
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4 crescent
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4 cosmic
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4 wolf
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4 sitting
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3 salamander
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3 dog
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3 grass
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3 ball
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3 branch
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3 fish
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3 cat
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3 earth
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3 pyramid
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3 yang
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3 fox
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3 globe
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3 yin
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3 lion
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3 planet
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3 wearing
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3 over
|
| 64 |
+
3 monkey
|
| 65 |
+
3 person
|
| 66 |
+
3 spiral
|
| 67 |
+
3 river
|
| 68 |
+
3 sheep
|
| 69 |
+
3 skull
|
| 70 |
+
2 bamboo
|
| 71 |
+
2 bear
|
| 72 |
+
2 raccoon
|
| 73 |
+
2 crown
|
| 74 |
+
2 otter
|
| 75 |
+
2 bull
|
| 76 |
+
2 wall
|
| 77 |
+
2 under
|
| 78 |
+
2 flying
|
| 79 |
+
2 lantern
|
| 80 |
+
2 owl
|
| 81 |
+
2 standing
|
| 82 |
+
2 elephant
|
| 83 |
+
2 paved
|
| 84 |
+
2 flag
|
| 85 |
+
2 hanging
|
| 86 |
+
2 donkey
|
| 87 |
+
2 waterfall
|
| 88 |
+
2 sunflower
|
| 89 |
+
2 squid
|
| 90 |
+
2 cup
|
| 91 |
+
2 armor
|
| 92 |
+
2 from
|
| 93 |
+
2 meerkat
|
| 94 |
+
2 city
|
| 95 |
+
1 triangle
|
| 96 |
+
1 sloth
|
| 97 |
+
1 snail
|
| 98 |
+
1 glass
|
| 99 |
+
1 panda
|
| 100 |
+
1 tiger
|
| 101 |
+
1 fountain
|
| 102 |
+
1 animal
|
| 103 |
+
1 algea
|
| 104 |
+
1 ray
|
| 105 |
+
1 lamb
|
| 106 |
+
1 orange
|
| 107 |
+
1 perched
|
| 108 |
+
1 pumpkin
|
| 109 |
+
1 manta
|
| 110 |
+
1 axolotl
|
| 111 |
+
1 zapus
|
| 112 |
+
1 pentastar
|
| 113 |
+
1 phone
|
| 114 |
+
1 yak
|
| 115 |
+
1 brick
|
| 116 |
+
1 candle
|
| 117 |
+
1 devilwingsand
|
| 118 |
+
1 giraffe
|
| 119 |
+
1 zebra
|
| 120 |
+
1 four
|
| 121 |
+
1 bee
|
| 122 |
+
1 season
|
| 123 |
+
1 building
|
| 124 |
+
1 five
|
| 125 |
+
1 starfish
|
| 126 |
+
1 warthog
|
| 127 |
+
1 turtle
|
| 128 |
+
1 shaped
|
| 129 |
+
1 wool
|
| 130 |
+
1 unicorn
|
| 131 |
+
1 frog
|
| 132 |
+
1 land
|
| 133 |
+
1 tower
|
| 134 |
+
1 middle
|
| 135 |
+
1 cathedral
|
| 136 |
+
1 wasp
|
| 137 |
+
1 butterfly
|
| 138 |
+
1 head
|
| 139 |
+
1 watermellon
|
| 140 |
+
1 his
|
| 141 |
+
1 bag
|
| 142 |
+
1 leave
|
| 143 |
+
1 corn
|
| 144 |
+
1 crab
|
| 145 |
+
1 hermit
|
| 146 |
+
1 people
|
| 147 |
+
1 space
|
| 148 |
+
1 floating
|
| 149 |
+
1 dragon
|
| 150 |
+
1 caterpillan
|
| 151 |
+
1 key
|
| 152 |
+
1 bowl
|
| 153 |
+
1 fruit
|
| 154 |
+
1 burning
|
| 155 |
+
1 eagle
|
| 156 |
+
1 disco
|
| 157 |
+
1 scorpio
|
| 158 |
+
1 awk
|
| 159 |
+
1 monocle
|
| 160 |
+
1 duck
|
| 161 |
+
1 flower
|
| 162 |
+
1 crow
|
| 163 |
+
1 door
|
| 164 |
+
1 house
|
| 165 |
+
1 woman
|
| 166 |
+
1 hippo
|
| 167 |
+
1 up
|
| 168 |
+
1 fossa
|
| 169 |
+
1 prairie
|
| 170 |
+
1 gorilla
|
| 171 |
+
1 toucan
|
| 172 |
+
1 card
|
| 173 |
+
1 beaver
|
| 174 |
+
1 wood
|
| 175 |
+
1 crane
|
| 176 |
+
1 bridge
|
| 177 |
+
1 stump
|
| 178 |
+
1 alpaca
|
| 179 |
+
1 hybrid
|
| 180 |
+
1 badger
|
| 181 |
+
1 sky
|
| 182 |
+
1 comet
|
| 183 |
+
1 desert
|
| 184 |
+
1 deamon
|
| 185 |
+
1 bunny
|
| 186 |
+
1 bubble
|
| 187 |
+
1 circul
|
| 188 |
+
1 python
|
| 189 |
+
1 snow
|
| 190 |
+
1 books
|
| 191 |
+
1 quetzal
|
| 192 |
+
1 tattoo
|
| 193 |
+
1 red
|
| 194 |
+
1 whale
|
| 195 |
+
1 of
|
| 196 |
+
1 tiny
|
| 197 |
+
1 parrot
|
| 198 |
+
1 drinking
|
| 199 |
+
1 climbing
|
| 200 |
+
1 six
|
| 201 |
+
1 reflexion
|
| 202 |
+
1 skunk
|
| 203 |
+
1 mouse
|
| 204 |
+
1 beetle
|
| 205 |
+
1 seahorse
|
| 206 |
+
1 jellyfish
|
| 207 |
+
1 hat
|
| 208 |
+
1 mammoth
|
| 209 |
+
1 jackalope
|
| 210 |
+
1 hedgehog
|
| 211 |
+
1 smoking
|
| 212 |
+
1 table
|
| 213 |
+
1 at
|
| 214 |
+
1 tusk
|
| 215 |
+
1 windmill
|
| 216 |
+
1 floor
|
| 217 |
+
1 berret
|
| 218 |
+
1 lynx
|
| 219 |
+
1 koala
|
| 220 |
+
1 heron
|
| 221 |
+
1 peacock
|
| 222 |
+
1 leaf
|
| 223 |
+
```
|
| 224 |
+
|
| 225 |
+
## Sorted alphabetically
|
| 226 |
+
|
| 227 |
+
```txt
|
| 228 |
+
Count Name
|
| 229 |
+
----- ----
|
| 230 |
+
87 a
|
| 231 |
+
1 algea
|
| 232 |
+
1 alpaca
|
| 233 |
+
13 an
|
| 234 |
+
12 and
|
| 235 |
+
1 animal
|
| 236 |
+
9 antler
|
| 237 |
+
2 armor
|
| 238 |
+
6 art
|
| 239 |
+
1 at
|
| 240 |
+
1 awk
|
| 241 |
+
1 axolotl
|
| 242 |
+
1 badger
|
| 243 |
+
1 bag
|
| 244 |
+
3 ball
|
| 245 |
+
2 bamboo
|
| 246 |
+
2 bear
|
| 247 |
+
1 beaver
|
| 248 |
+
1 bee
|
| 249 |
+
1 beetle
|
| 250 |
+
1 berret
|
| 251 |
+
10 bird
|
| 252 |
+
1 books
|
| 253 |
+
1 bowl
|
| 254 |
+
3 branch
|
| 255 |
+
1 brick
|
| 256 |
+
1 bridge
|
| 257 |
+
1 bubble
|
| 258 |
+
5 bug
|
| 259 |
+
1 building
|
| 260 |
+
2 bull
|
| 261 |
+
1 bunny
|
| 262 |
+
1 burning
|
| 263 |
+
1 butterfly
|
| 264 |
+
1 candle
|
| 265 |
+
1 card
|
| 266 |
+
3 cat
|
| 267 |
+
1 caterpillan
|
| 268 |
+
1 cathedral
|
| 269 |
+
13 circle
|
| 270 |
+
1 circul
|
| 271 |
+
2 city
|
| 272 |
+
1 climbing
|
| 273 |
+
12 cloud
|
| 274 |
+
10 coin
|
| 275 |
+
1 comet
|
| 276 |
+
6 concept
|
| 277 |
+
1 corn
|
| 278 |
+
4 cosmic
|
| 279 |
+
1 crab
|
| 280 |
+
1 crane
|
| 281 |
+
4 crescent
|
| 282 |
+
1 crow
|
| 283 |
+
2 crown
|
| 284 |
+
2 cup
|
| 285 |
+
1 deamon
|
| 286 |
+
6 deer
|
| 287 |
+
1 desert
|
| 288 |
+
1 devilwingsand
|
| 289 |
+
1 disco
|
| 290 |
+
3 dog
|
| 291 |
+
2 donkey
|
| 292 |
+
1 door
|
| 293 |
+
1 dragon
|
| 294 |
+
1 drinking
|
| 295 |
+
1 duck
|
| 296 |
+
1 eagle
|
| 297 |
+
3 earth
|
| 298 |
+
2 elephant
|
| 299 |
+
5 feather
|
| 300 |
+
3 fish
|
| 301 |
+
1 five
|
| 302 |
+
2 flag
|
| 303 |
+
1 floating
|
| 304 |
+
1 floor
|
| 305 |
+
1 flower
|
| 306 |
+
2 flying
|
| 307 |
+
1 fossa
|
| 308 |
+
1 fountain
|
| 309 |
+
1 four
|
| 310 |
+
3 fox
|
| 311 |
+
1 frog
|
| 312 |
+
2 from
|
| 313 |
+
1 fruit
|
| 314 |
+
1 giraffe
|
| 315 |
+
1 glass
|
| 316 |
+
3 globe
|
| 317 |
+
1 gorilla
|
| 318 |
+
3 grass
|
| 319 |
+
2 hanging
|
| 320 |
+
1 hat
|
| 321 |
+
1 head
|
| 322 |
+
1 hedgehog
|
| 323 |
+
1 hermit
|
| 324 |
+
1 heron
|
| 325 |
+
1 hippo
|
| 326 |
+
1 his
|
| 327 |
+
9 holding
|
| 328 |
+
5 horn
|
| 329 |
+
1 house
|
| 330 |
+
1 hybrid
|
| 331 |
+
6 in
|
| 332 |
+
1 jackalope
|
| 333 |
+
1 jellyfish
|
| 334 |
+
1 key
|
| 335 |
+
1 koala
|
| 336 |
+
1 lamb
|
| 337 |
+
1 land
|
| 338 |
+
11 landscape
|
| 339 |
+
2 lantern
|
| 340 |
+
1 leaf
|
| 341 |
+
1 leave
|
| 342 |
+
17 leaves
|
| 343 |
+
3 lion
|
| 344 |
+
1 lynx
|
| 345 |
+
1 mammoth
|
| 346 |
+
1 manta
|
| 347 |
+
2 meerkat
|
| 348 |
+
1 middle
|
| 349 |
+
3 monkey
|
| 350 |
+
1 monocle
|
| 351 |
+
13 moon
|
| 352 |
+
7 mountain
|
| 353 |
+
1 mouse
|
| 354 |
+
1 of
|
| 355 |
+
9 on
|
| 356 |
+
1 orange
|
| 357 |
+
2 otter
|
| 358 |
+
3 over
|
| 359 |
+
2 owl
|
| 360 |
+
1 panda
|
| 361 |
+
1 parrot
|
| 362 |
+
2 paved
|
| 363 |
+
1 peacock
|
| 364 |
+
1 pentastar
|
| 365 |
+
1 people
|
| 366 |
+
1 perched
|
| 367 |
+
3 person
|
| 368 |
+
1 phone
|
| 369 |
+
3 planet
|
| 370 |
+
1 prairie
|
| 371 |
+
1 pumpkin
|
| 372 |
+
3 pyramid
|
| 373 |
+
1 python
|
| 374 |
+
1 quetzal
|
| 375 |
+
4 rabbit
|
| 376 |
+
2 raccoon
|
| 377 |
+
1 ray
|
| 378 |
+
1 red
|
| 379 |
+
1 reflexion
|
| 380 |
+
3 river
|
| 381 |
+
3 salamander
|
| 382 |
+
1 scorpio
|
| 383 |
+
1 seahorse
|
| 384 |
+
1 season
|
| 385 |
+
1 shaped
|
| 386 |
+
3 sheep
|
| 387 |
+
4 sitting
|
| 388 |
+
1 six
|
| 389 |
+
3 skull
|
| 390 |
+
1 skunk
|
| 391 |
+
1 sky
|
| 392 |
+
1 sloth
|
| 393 |
+
1 smoking
|
| 394 |
+
1 snail
|
| 395 |
+
1 snow
|
| 396 |
+
1 space
|
| 397 |
+
3 spiral
|
| 398 |
+
2 squid
|
| 399 |
+
2 standing
|
| 400 |
+
5 star
|
| 401 |
+
1 starfish
|
| 402 |
+
5 stick
|
| 403 |
+
1 stump
|
| 404 |
+
7 sun
|
| 405 |
+
2 sunflower
|
| 406 |
+
85 symmetry
|
| 407 |
+
1 table
|
| 408 |
+
1 tattoo
|
| 409 |
+
9 the
|
| 410 |
+
4 three
|
| 411 |
+
1 tiger
|
| 412 |
+
1 tiny
|
| 413 |
+
1 toucan
|
| 414 |
+
1 tower
|
| 415 |
+
13 tree
|
| 416 |
+
1 triangle
|
| 417 |
+
1 turtle
|
| 418 |
+
1 tusk
|
| 419 |
+
15 two
|
| 420 |
+
2 under
|
| 421 |
+
1 unicorn
|
| 422 |
+
1 up
|
| 423 |
+
2 wall
|
| 424 |
+
1 warthog
|
| 425 |
+
1 wasp
|
| 426 |
+
10 water
|
| 427 |
+
2 waterfall
|
| 428 |
+
1 watermellon
|
| 429 |
+
3 wearing
|
| 430 |
+
1 whale
|
| 431 |
+
1 windmill
|
| 432 |
+
6 wings
|
| 433 |
+
13 with
|
| 434 |
+
4 wolf
|
| 435 |
+
1 woman
|
| 436 |
+
1 wood
|
| 437 |
+
1 wool
|
| 438 |
+
1 yak
|
| 439 |
+
3 yang
|
| 440 |
+
3 yin
|
| 441 |
+
1 zapus
|
| 442 |
+
1 zebra
|
| 443 |
+
```
|
silvery_trait_v3.ckpt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4b0308cf699caf50120d43748134b9cfbf9ac0bc40fa8c29759a52e5ae25f253
|
| 3 |
+
size 2132856686
|