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Installation

This package requires Python 3.10 or later and PyTorch 2.5 or later for execution. PyTorch must be installed according to your CUDA version. A GPU with more than 8GB of VRAM is recommended. While it can run on a CPU, please note that the processing is not currently optimized for CPUs, which may result in longer execution times.

from PYPI

pip install yomitoku

using uv

This repository uses the package management tool uv. After installing uv, clone the repository and execute the following commands:

uv sync

Using GPU with onnxruntime 

uv sync --extra gpu

When using uv, you need to modify the following part of the pyproject.toml file to match your CUDA version. By default, PyTorch compatible with CUDA 12.4 will be downloaded.

[[tool.uv.index]]
name = "pytorch-cuda124"
url = "https://download.pytorch.org/whl/cu124"
explicit = true

using docker

A Dockerfile is provided in the root of the repository, which you are welcome to use.

docker build -t yomitoku .

docker run -it --gpus all -v $(pwd):/workspace --name yomitoku yomitoku /bin/bash

docker run -it -v $(pwd):/workspace --name yomitoku yomitoku /bin/bash