description: <p>My favorite catgirl in the world.</p><p><strong>Request for comments.</strong></p><p></p><p>Twitter:<a target="_blank" rel="ugc" href="https://twitter.com/Ebycow">https://twitter.com/Ebycow</a></p>
modelVersions.availability: Public
modelVersions.baseModel: SD 1.5
modelVersions.baseModelType: Standard
modelVersions.description: <p># Overview</p><p>I have reduced the dimensionality from 256 to 64 (a typical level) compared to V1. Which is more appropriate may depend on the backend used.<br />I trained a lightweight model on a similar dataset, and while the overall quality is nearly the same, I can't discern any differences in the details.</p><pre><code>train_network.py --pretrained_model_name_or_path="JosephusCheung/ACertainty" --prior_loss_weight=1.0 --enable_bucket --min_bucket_reso=384 --max_bucket_reso=1280 --train_batch_size=8 --learning_rate=1e-6 --text_encoder_lr 5e-8 --xformers --save_model_as=safetensors --clip_skip=2 --seed=42 --color_aug --flip_aug --network_module=networks.lora --resolution=768,512 --network_dim 64 --save_every_n_epochs 1 --max_train_epochs 2</code></pre>
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modelVersions.name: v2.0
modelVersions.publishedAt: 2023-07-14T08:38:57.499Z
modelVersions.trainedWords: vanilla
modelVersions.availability: Public
modelVersions.baseModel: SD 1.5
modelVersions.baseModelType: Standard
modelVersions.description: <p># Training summary</p><p>This model was trained by using 40 manually sampled images for 10 epochs, with 100 iterations per epoch.</p><p>The following is an excerpt of some of the learning commands by sd-script for reference</p><pre><code>train_network.py --pretrained_model_name_or_path="JosephusCheung/ACertainty" --prior_loss_weight=1.0 --enable_bucket --min_bucket_reso=384 --max_bucket_reso=1280 --train_batch_size=12 --learning_rate=1e-4 --text_encoder_lr 5e-5 --use_8bit_adam --xformers --mixed_precision=fp16 --save_every_n_epochs=10 --save_model_as=safetensors --clip_skip=2 --seed=42 --color_aug --flip_aug --network_module=networks.lora --resolution=768,512 --network_dim 256 --max_train_epochs 4 --shuffle_caption</code></pre><p># Problems<br />This model is a bit overfitted, but it works comfortably with an intensity of around 0.5-0.7 depending on the model. <br />I'm looking for information about optimal parameter information for character learning with LoRA. Also, if you have a request for a LoRA model using large-scale data, please contact us. The challenge now is to acquire that know-how.</p>
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modelVersions.trainedWords: vanilla
name: Vanilla (Nekopara) - バニラ (ネコぱら)
tags: anime character girl catgirls video game