The mini version of fastai's miniai PyTorch framework created during the fastai course 2022-2023.

pip install minai

or to install from source clone this repo and run:

pip install -e .

This is still a work in progress - I'll add example usage soon. But in general, for examples from the course where you have from miniai.something import X you should be able to do from minai import X. You can do import minai as mi or even from minai import * for quick access to all the functions and things, if you're so inclined.

Tutorial 1 has a minimal example of fitting a model using minai - open it in Google colab here.

Tutorial 2 shows callbacks in action on a slightly more complex task - open it in Google colab here.

An example of the library in action: this notebook shows how to train a diffusion model on spectrograms to generate birdcalls, using minai. It is covered in the final lesson of Part 2 of the FastAI course.

And a lovely demo of use in the wild is this report by Thomas Capelle where he uses diffusion models to predict the next frame of an image sequence.