readme: ---
  language:
  - en
  thumbnail: "https://huggingface.co/KnightMichael/yagamitaichi/resolve/main/README-FILES/yagamitaichi-thumbnail.jpg"
  datasets:
  - KnightMichael/yagamitaichi
  tags:
  - yagami-taichi
  - tai-kamiya
  - hypernetwork
  - boy
  - character
  - model
  - digimon
  - adventure
  - "1999"
  - anime
  - anything-3.0
  - stable-diffusion
  - text-to-image
  - deepbooru
  - tags
  - 1boy
  ---
  
  # Yagami Taichi (Tai Kamiya) Hypernetwork Boy Character Model from Digimon Adventure (1999) Anime for Anything 3.0
  
  ![Yagami Taichi (Tai Kamiya)](/KnightMichael/yagamitaichi/resolve/main/README-FILES/yagamitaichi.webp)
  
  # Base Model
  
  - Checkpoint: [Anything-V3.0-pruned.ckpt](/Linaqruf/anything-v3.0/blob/main/Anything-V3.0-pruned.ckpt)
  - VAE: [Anything-V3.0.vae.pt](/Linaqruf/anything-v3.0/blob/main/Anything-V3.0.vae.pt)
  
  # Hypernetwork Parameters
  
  - Modules: 768, 1024, 320, 640, 1280
  - Layer structure: 1, 2, 1
  - Activation function: Linear
  - Layer weights initialization: Normal
  - Layer normalization: No
  - Dropout: No
  
  # Training Parameters
  
  - Learning rate: 0.00001
  - Batch size: 1
  - Gradient accumulation steps: 1
  - Dataset: [yagamitaichi](/datasets/KnightMichael/yagamitaichi)
  - Prompt template file: [hypernetwork.txt](README-FILES/hypernetwork.txt)
  - Width: 512
  - Height: 512
  - Steps: [100000](yagamitaichi-100000.pt), [125000](yagamitaichi-125000.pt), [150000](yagamitaichi-150000.pt), [175000](yagamitaichi-175000.pt), [200000](yagamitaichi-200000.pt)
  
  # Dataset Creation
  
  - 296 images of Tai alone captured from episodes 1 to 21.
  - Manually cropped to 1:1 and resized to 512x512 using Birme.
  - Automatically tagged by DeepBooru.
  
  # How to Use
  
  [Recommended Colab](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb)
  
  1. Set up the [Anything 3.0](/Linaqruf/anything-v3.0) model. I will specifically use the model [Anything-V3.0-pruned.ckpt](/Linaqruf/anything-v3.0/blob/main/Anything-V3.0-pruned.ckpt), since it was the same model that I used for training the hypernetwork. In the [recommended Colab](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb), paste the following link in the "Link_CKPT" field and execute all cells except the last one:
     
     ```
     https://huggingface.co/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0-pruned.ckpt
     ```
     
  2. Optional, but recommended: Set up the [Anything 3.0 VAE](/Linaqruf/anything-v3.0/blob/main/Anything-V3.0.vae.pt). The hypernetwork model was trained using this VAE, but is not 100% necessary. However, the examples shown here were generated using it. The most significant difference I have noticed is more vivid colors in generated images when using the VAE. In the [recommended Colab](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb), add a new code cell, paste the following command line inside and execute it:
     
     ```
     !wget -O /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/VAE/Anything-V3.0.vae.pt https://huggingface.co/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0.vae.pt
     ```
     
  3. Set up the desired hypernetwork model PT file. There are 5 different models. The number in the file name indicates the amount of training steps. I recommend to use the model with highest number of steps, since it was training for a longer time. If you want to compare the training steps performance, feel free to try the other models too. The examples shown here were generated using the 200000 steps version.
     
     - [yagamitaichi-200000.pt (Recommended)](yagamitaichi-200000.pt)
     - [yagamitaichi-175000.pt](yagamitaichi-175000.pt)
     - [yagamitaichi-150000.pt](yagamitaichi-150000.pt)
     - [yagamitaichi-125000.pt](yagamitaichi-125000.pt)
     - [yagamitaichi-100000.pt](yagamitaichi-100000.pt)
     
     In the [recommended Colab](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb), add a new code cell, paste the following command lines inside and execute it:
     
     ```
     !mkdir /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/hypernetworks
     !wget -O /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/hypernetworks/yagamitaichi-200000.pt https://huggingface.co/KnightMichael/yagamitaichi/resolve/main/yagamitaichi-200000.pt
     ```
     
  4. In the [recommended Colab](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb), now you can execute the last cell, wait until the link to the web UI appears and get in.
     
  5. In the web UI, go to "Settings" tab and set the following:
     
     - SD VAE to the Anything VAE. (Only if you did the step 2)
     - Hypernetwork to the "yagamitaichi" model.
     
     Then, click the "Apply settings" button.
     
  # Prompting
  
  Include in your prompt the tags contained in the [dataset](/datasets/KnightMichael/yagamitaich