Aim
Deploy Aim to track AI metadata, helping you compare prompts and develop experiments iteratively
PyTorch Jupyter Notebook
Deploy a Jupyter Notebook configured with PyTorch to develop and run machine learning applications interactively.
- CategoryStarter
- AuthorKoyeb
- Website
- Repositorygithub.com/koyeb/example-pytorch-jupyter
- TechnologiesPyTorch, Jupyter Notebooks, Docker
Overview
Jupyter Notebooks are web-based interactive computing projects for Python. They allow you to interactively develop, run, and share Python applications combined with explanatory content. Jupyter Notebooks are ideal for teaching or presentation contexts where you can update and run code in real time, interleave contextual information with the code, and collaborate on data science projects.
PyTorch is an open-source framework for building deep learning models using GPUs and CPUs. PyTorch uses the Torch library under the hood, allowing users to perform tensor computation and automatic differentiation using dynamic computational graphs.
This Starter deploys a Jupyter Notebook running PyTorch to demonstrate how to run an interactive PyTorch environment on Koyeb. By default, the project deploys on a RTX 4000 SFF ADA GPU.
Configuration
The following environment variable may optionally be configured when deploying this one-click:
JUPYTER_PASSWORD: The password to set to authenticate to the Jupyter Notebook web interface. Remove this environment variable if you wish to deploy without a password.
