• Inspect ML models visually from your Python notebook 📗
• Review ML models collaboratively to get feedback on potential errors 🧐
• Test ML models automatically for a safe deployment to production ⛑

git clone https://github.com/Giskard-AI/giskard.git
cd giskard
docker-compose up -d

After the application is started you can access at:

http://localhost:19000

login / password: admin / admin

• docker
• docker-compose

You can upload models to Giskard from Jupyter notebooks or any other python environment. it can be done using Giskard client library

There's a demo python notebook available at http://localhost:18888 that can be used to upload a first model.

Find out more about Giskard by reading our docs

Join our community on Discord to get support and leave feedback