This repository contains Jupyter notebook examples to showcase Datalayer Run. Datalayer Run allows you to scale Jupyter Kernels from your local JupyterLab on your machine to the cloud, including running your Kernels on GPU.
First, clone this repository.
git clone https://github.com/datalayer/examples.git datalayer-examples
cd datalayer-examplesTo try the examples, we recommend creating a very simple conda environment (with Python and JupyterLab) thanks to the following commands.
ENV_NAME=datalayer-examples
# conda deactivate && conda remove -y --all -n $ENV_NAME # Delete if it already exists.
conda env create --solver=libmamba -n $ENV_NAME -f ./environment.yaml
conda activate $ENV_NAME
jupyter labAlternatively, you can just install the jupyter-kernels package in your existing environment with pip install jupyter-kernels (this will install JupyterLab version 4.0.10).
Read the documentation website to know more how to scale your local notebooks to the cloud.
Don't worry, it is easy 👍. You just need to create an account, click on the Datalayer Run tile in the JupyterLab launcher, wait a bit for your Kernels to be ready, and then just assign a Remote Kernel from any Notebook kernel picker.
The examples of this repository showcase the execution of code remotely from your local JupyterLab in various case as shown on the following picture.
Simple Python example.
Titanic example.
CUDA vector addition example.
cuDF example.
PyTorch example.
Detect faces from this famous video.
LLMA example.