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See the tutorial for how to load and use these.\n\n## Preprint\nPlease cite https://www.biorxiv.org/content/10.1101/2024.10.09.617507v3. Also see https://github.com/Genentech/decima-applications for all the code used to train and apply models in this preprint.\n\n## Requirements\nDecima has been tested on Ubuntu 24.04.3 and MacOS 15.6.1 using Python 3.9-3.12.\n\n## Installation\n\nInstall the package from PyPI,\n\n```sh\npip install decima\n```\n\nOr if you want to be on the cutting edge,\n\n```sh\npip install git+https://github.com/genentech/decima.git@main\n```\nTypical installation time including all dependencies is under 10 minutes.\n\n## Tutorials\nSee the [tutorials](docs/tutorials) for instructions, including how to train your own Decima model with an example dataset.\n\n\u003c!-- biocsetup-notes --\u003e\n\n## Note\n\nThis project has been set up using [BiocSetup](https://github.com/biocpy/biocsetup)\nand [PyScaffold](https://pyscaffold.org/).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenentech%2Fdecima","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgenentech%2Fdecima","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenentech%2Fdecima/lists"}