PyPI 官网下载 | mimikit-0.1.10.tar.gz

# mimikit Do deep-learning on your own audio files like a pro with just a google account. `mimikit` is a music modelling kit that lets you mimic / transform your own audio files with generative neural-networks. It contains a collection of models in pytorch and pytorch-lightning as well as powerful ways to : - prepare & store your data for these models - train the models online by free gpu providers - store and track every experiment you make & every sound bits you generate on neptune.ai - also for free ----- **Table of Contents** * [Installation](#installation) * [Quickstart](#quickstart) * [Usage](#usage) * [Documentation](#documentation) * [Contribute](#contribute) * [License](#license) ## Installation mimikit is available as a `pip` package. Open a terminal and type : ```bash $ pip install mimikit ``` ## Quickstart If you never did deep-learning before, we recommend you start with the [quickest intro to practical deep-learning ever]() - Have a [google account](https://accounts.google.com/signup/v2/webcreateaccount?flowName=GlifWebSignIn&flowEntry=SignUp) and register with it to [neptune.ai](https://neptune.ai/) - Put some audio files in your google drive or [make a database]() on your computer - Open the [FreqNet starter notebook](https://colab.research.google.com/github/k-tonal/mmk-notebooks/blob/main/FreqNet.ipynb) in colab and follow the instructions For more, check out the [mimikit-notebooks](https://github.com/k-tonal/mimikit-notebooks), the [mmikit docs]() or the documentation for the [freqnet package]() ## Usage Check out the [mimikit-notebooks](https://github.com/k-tonal/mimikit-notebooks) for client code examples ## Documentation TODO ! ## Contribute `mimikit` welcomes all kinds of contributions! From bug-fixes to new cool experimental models or improving coverage of tests and docs : get in touch and/or make a pull request. ## License mimikit is distributed under the terms of the [GNU General Public License v3.0](https://choosealicense.com/licenses/gpl-3.0/)