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UrangDiffusion v2.5

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2.1k
53
Updated: Dec 4, 2024
base modelanimewomangame charactergirlsman
Download (6.62 GB)
Verified:
SafeTensor
Type
Checkpoint Trained
Stats
204
Reviews
(27)
Published
Dec 4, 2024
Base Model
SDXL 1.0
Training
Epochs: 10
Hash
AutoV2
91F0729DB0
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Sleepless Nights
kayfahaarukku's Avatar
kayfahaarukku
License:
CreativeML Open RAIL++-MAddendum

UrangDiffusion v2.5 (oo-raw-ng Diffusion) brings a whole-new training method compared to the v2.0. The model provide more flexibility and brings some updated dataset.

The name “Urang” comes from Sundanese, meaning “We/Our/I.” The history behind the name is to make the model not only suitable for me but also for many people. Another reason is that I use many resources (training scripts, dataset collecting scripts, etc.) from other people. It’s unfair to claim this model as “my sole work.”

Standard Prompting Guidelines

The model is finetuned from Animagine XL 3.1, which is trained with danbooru tags. However, there is a little bit changes on dataset captioning, therefore there is some different default prompt used:

  • Default prompt: 1girl/1boy, character name, from what series, everything else in any order, masterpiece, best quality, high score, great score, absurdres.

  • Default negative prompt: lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, low score, bad score, average score, signature, watermark, username, blurry,

  • Default configuration: Euler a with around 25-30 steps, CFG 5-7, and ENSD set to 31337. Sweet spot is around 25 steps and CFG 7.

Training Configurations

Finetuned from: UrangDiffusion v2.0

Pretraining I (Crashed mid training):

  • Dataset size: ~50,300 images

  • GPU: 1xH100 80GB

  • Optimizer: AdaFactor

  • Unet Learning Rate: 3.75e-6

  • Text Encoder Learning Rate: 1.875e-6

  • Batch Size: 16

  • Gradient Accumulation: 3

  • Warmup steps: 100 steps

  • Min SNR: 5

  • Epoch: 4

  • Random Cropping: True

  • Loss: Huber

  • Huber Schedule: SNR

  • Huber C: 0.1

Pretraining II (Continue from epoch 4):

  • Dataset size: ~50,300 images

  • GPU: 1xA100 80GB

  • Optimizer: AdaFactor

  • Unet Learning Rate: 3.75e-6

  • Text Encoder Learning Rate: 1.875e-6

  • Batch Size: 16

  • Gradient Accumulation: 3

  • Warmup steps: 100 steps

  • Min SNR: 5

  • Epoch: 6

  • Random Cropping: True

  • Loss: Huber

  • Huber Schedule: SNR

  • Huber C: 0.1

CyberFix:

Epoch 10 + (Cyberrealistic XL v3.1 - SDXL 1.0 Base) = Temp

Temp model's text encoder changed with Epoch 10's text encoder.

Added/Updated Series, Characters, and Styles

v2.5

Artists:

  1. ningen mame

  2. ciloranko

  3. rhasta

  4. atdan

  5. sho (sho lwlw)

  6. tianliang

  7. duohe

  8. fangdongye

  9. chen bin

  10. ishikei

  11. ask (askzy)

  12. wlop

  13. tsurusaki takahiro

  14. kokosando

  15. wagashi (dagashiya)

  16. nawakena

  17. kedama milk

  18. hiten (hitenkei)

  19. matanonki

  20. sy4

  21. houraku

  22. fuzichoco

  23. sencha (senchat)

  24. rei (sanbonzakura)

  25. houkisei

  26. alp

  27. dino (dinoartforame)

  28. kuroduki (pieat)

  29. maeda hiroyuki

  30. tabi (tabisumika)

  31. yuumei

  32. rella

  33. konya

  34. karasue

  35. hoshi (snacherubi)

  36. modare

  37. creayus

  38. reoen

  39. kawacy

  40. wanke

  41. kousaki rui

  42. chyoel

  43. lpip

  44. kaninn

  45. azuuru

  46. mignon

  47. amazuyu

  48. tatsuki

  49. shiro9jira

  50. novelance

  51. lack

  52. airseal

  53. huanxiang

  54. heitu

  55. rsef

  56. machi (machi0910)

  57. meion

  58. z3zz4

  59. ame (uten cancel)

  60. healthyman

  61. wagashi (dagashiya)

  62. yamamoto souichirou

  63. freng

  64. kaede (sayappa)

  65. masaki (ekakiningen)

  66. asakuraf

  67. misaka 12003-gou

  68. hood (james x)

  69. as109

  70. yd (orange maru)

  71. void 0

  72. fajyobore

  73. alphonse (white datura)

  74. akita hika

  75. nanaken

  76. nana

  77. muchi

  78. maro

  79. shisoneri

  80. tottotonero

  81. mochirong

  82. nixeu

  83. fujiyama

  84. qizhu

  85. kase daiki

  86. ke-ta

  87. tidsean

  88. aki99

  89. hitsukuya

  90. shimmer

  91. morikura en

  92. ringeko-chan

  93. pottsness

  94. torino aqua

  95. zelitto

  96. personal ami

  97. lm7 (op-center)

  98. quan (kurisu tina)

  99. migolu

  100. shiki (psychedelic g2)

  101. mizumizuni

  102. kita (kitairoha)

  103. kousaki rui

  104. mofu

  105. namako

  106. omone

  107. hokoma

  108. agm

  109. tab head

  110. neoartcore

  111. sciamano240

  112. kuroboshi kouhaku

  113. huke

  114. lam (ramdayo)

  115. nyori

  116. yano mitsuki (nanairo)

  117. yatomi

  118. amashiro natsuki

  119. yukisame

  120. mishima kurone

  121. teshima nari

  122. shigure ui

  123. orobou

v2.0

Series:

  1. zenless zone zero

  2. wuthering waves

  3. sewayaki kitsune no senko-san

Honkai: Star Rail:

  1. firefly

  2. acheron

  3. sparkle

  4. robin

  5. aventurine

  6. black swan

  7. feixiao

  8. yunli

  9. lingsha

  10. march 7th (hunt)

  11. jade

  12. jiaoqiu

  13. gallagher

  14. rappa

  15. misha

Hololive Talents:

  1. hololive indonesia

  2. raora panthera

  3. elizabeth rose bloodflame

  4. gigi murin

  5. cecilia immergreen

Genshin Impact:

  1. arlecchino

  2. clorinde

  3. chiori

  4. mualani

  5. xianyun

  6. sigewinne

  7. kinich

  8. xilonen

  9. emilie

  10. gaming

  11. kachina

  12. sethos

Others:

  1. landscape

  2. several concepts to fix anatomy issue

Special Thanks

  • My co-workers(?) at CagliostroLab for the insights and feedback.

  • Nur Hikari and Vanilla Latte for quality control.

  • Linaqruf, my tutor and role model in AI-generated images, and also the person behind tag ordering.

License

UrangDiffusion falls under the Fair AI Public License 1.0-SD license.