ludwig-getting-started

Declarative ML examples with Ludwig

Compile Python and Create VirtualEnv with It

sudo apt-get install build-essential gdb lcov libbz2-dev libffi-dev libgdbm-dev liblzma-dev libncurses5-dev libreadline6-dev libsqlite3-dev libssl-dev lzma lzma-dev tk-dev uuid-dev zlib1g-dev

wget https://www.python.org/ftp/python/3.10.5/Python-3.10.5.tgz

tar zxvf Python-3.10.5.tgz

./configure --enable-optimizations

make -j 32

make altinstall

Create virtualenv and source

/usr/local/bin/python -m venv ~/.venv

vim ~/.bashrc and add line: source ~/.venv/bin/activate

Example of Getting Started

1. wget https://ludwig-ai.github.io/ludwig-docs/0.5/data/rotten_tomatoes.csv
2. Create yaml file (to train) rotten_tomatoes.csv
3. Train: ludwig train --config rotten_tomatoes.yaml --dataset rotten_tomatoes.csv

Training on m1ultra studio

make install-mac make train-ludwig finishes in: 39.21 real 123.35 user 60.05 sys

References

• Watch Walkthrough on YouTube with M1Ultra Mac
• O'Reilly: Training Ludwig Declarative Deep Learning models using Mac Studio M1Ultra