Upload 4 files
Browse files- .gitattributes +1 -1
- README.md +124 -0
- demo.png +3 -0
- hololive_wd15.yaml +68 -0
.gitattributes
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.wasm filter=lfs diff=lfs merge=lfs -text
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.tflite filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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demo.png filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: other
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---
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# Model Card for Model ID
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hololive-diffusion, a stable diffusion 2.1 768x768 model.
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Trained on ~73k hololive fanart images
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## License
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This model is a fine-tune of Waifu diffusion 1.5.
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hololive-diffusion is released under the Fair AI Public License 1.0-SD (https://freedevproject.org/faipl-1.0-sd/). If any derivative of this model is made, please share your changes accordingly. Special thanks to ronsor/undeleted (https://undeleted.ronsor.com/) for help with the license.
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When creating characters owned and copyrighted by cover corp, you may not use this model or any of its outputs in a way that is counter to Hololive's fanart guidelines: https://hololivepro.com/en/terms/
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## Prompting
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The start of the prompt should have all the following:
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"hololive, anime, waifu"
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Add one of danbooru's content ratings
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* general
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* sensitive
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* questionable
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* explicit
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and the character name
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### names
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The model was trained using the following names. These aren't necessarily hololive vtubers, and the characters with less popular artworks will be harder to get correct.
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* a-chan (hololive)
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* airani iofifteen
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* akai haato
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* aki rosenthal
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* allegro (hoshimachi suisei)
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* amane kanata
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* anemachi
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* anya melfissa
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* artia
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* avatar (holoearth)
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* ayunda risu
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* azki (hololive)
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* ceres fauna
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* civia
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* coco kaine
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* deadbeat (calliope mori)
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* doris (hololive)
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* enma-chan
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* gawr gura
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* haaton (akai haato)
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* hakos baelz
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* hakui koyori
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* harusaki nodoka
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* himemori luna
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* hoshimachi suisei
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* houshou marine
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* inugami korone
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* irys (hololive)
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* j-chad
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* kaela kovalskia
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* kagura nana
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* kazama iroha
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* kiryu coco
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* kobo kanaeru
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* kureiji ollie
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* kurokami fubuki
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* la+ darknesss
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* mama lillie
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* mano aloe
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* matsurisu
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* minato aqua
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* moku seiko
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* momosuzu nene
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* moona hoshinova
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* mori calliope
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* murasaki shion
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* nakiri ayame
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* nanashi mumei
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* natsuiro matsuri
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* nekomata okayu
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* ninomae ina'nis
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* nousagi (usada pekora)
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* omaru polka
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* omega alpha
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* ookami mio
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* oozora subaru
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* ouro kronii
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* pavolia reine
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* pekomama
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* roboco-san
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* sakamata chloe
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* sakura miko
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* shigure ui (vtuber)
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* shirakami fubuki
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* shiranui flare
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* shirogane noel
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* shishiro botan
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* spade echo
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* sukonbu (shirakami fubuki)
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* takanashi kiara
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* takane lui
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* takodachi (ninomae ina'nis)
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* tokino sora
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* tokoyami towa
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* tsukumo sana
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* tsunomaki watame
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* uruha rushia
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* usada pekora
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* vestia zeta
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* wahtcher (ninomae ina'nis)
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* watoto (mythbreakers)
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* watson amelia
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* yozora mel
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* yukihana lamy
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* yuul b alwright (mythbreakers)
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* yuzuki choco
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demo.png
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Git LFS Details
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hololive_wd15.yaml
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model:
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base_learning_rate: 1.0e-4
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target: ldm.models.diffusion.ddpm.LatentDiffusion
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params:
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parameterization: "v"
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linear_start: 0.00085
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linear_end: 0.0120
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num_timesteps_cond: 1
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log_every_t: 200
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timesteps: 1000
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first_stage_key: "jpg"
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cond_stage_key: "txt"
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image_size: 64
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channels: 4
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cond_stage_trainable: false
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conditioning_key: crossattn
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monitor: val/loss_simple_ema
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scale_factor: 0.18215
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use_ema: False # we set this to false because this is an inference only config
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unet_config:
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target: ldm.modules.diffusionmodules.openaimodel.UNetModel
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params:
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use_checkpoint: True
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use_fp16: True
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image_size: 32 # unused
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in_channels: 4
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out_channels: 4
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model_channels: 320
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attention_resolutions: [ 4, 2, 1 ]
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num_res_blocks: 2
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channel_mult: [ 1, 2, 4, 4 ]
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num_head_channels: 64 # need to fix for flash-attn
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use_spatial_transformer: True
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use_linear_in_transformer: True
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transformer_depth: 1
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context_dim: 1024
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legacy: False
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first_stage_config:
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target: ldm.models.autoencoder.AutoencoderKL
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params:
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embed_dim: 4
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monitor: val/rec_loss
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ddconfig:
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#attn_type: "vanilla-xformers"
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double_z: true
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z_channels: 4
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resolution: 256
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in_channels: 3
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out_ch: 3
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ch: 128
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ch_mult:
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- 1
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- 2
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- 4
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- 4
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num_res_blocks: 2
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attn_resolutions: []
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dropout: 0.0
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lossconfig:
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target: torch.nn.Identity
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cond_stage_config:
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target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
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params:
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freeze: True
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layer: "penultimate"
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