Kanji_project_multimodal.zip

: You can find similar existing multimodal resources on Kaggle or Hugging Face .

Once organized, compress the folder using your terminal or file manager: kanji_project_multimodal.zip

: Grayscale or binary images of characters (e.g., 64x64 pixels), often sourced from databases like ETL9G or Kuzushiji-MNIST . : You can find similar existing multimodal resources

Since this specific filename often refers to datasets used in multimodal machine learning , here is how you can structure and compile it: 1. Gather Your "Modalities" Gather Your "Modalities" : Sentence-level examples where the

: Sentence-level examples where the Kanji is used, which can be extracted from sources like Common Crawl . 2. Organize the Directory Structure

kanji_project_multimodal/ ├── data/ │ ├── images/ # .png or .jpg files (Visual) │ ├── strokes/ # .npz or .json files (Temporal/Sequence) │ └── text/ # .csv or .json metadata (Linguistic) ├── models/ # Pre-trained weights (if applicable) ├── notebooks/ # Data generation or training scripts └── README.md # Documentation and citations Use code with caution. Copied to clipboard 3. Zip the Project

A multimodal Kanji project usually requires at least two of the following:

: You can find similar existing multimodal resources on Kaggle or Hugging Face .

Once organized, compress the folder using your terminal or file manager:

: Grayscale or binary images of characters (e.g., 64x64 pixels), often sourced from databases like ETL9G or Kuzushiji-MNIST .

Since this specific filename often refers to datasets used in multimodal machine learning , here is how you can structure and compile it: 1. Gather Your "Modalities"

: Sentence-level examples where the Kanji is used, which can be extracted from sources like Common Crawl . 2. Organize the Directory Structure

A multimodal Kanji project usually requires at least two of the following: