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Quick Start
Here is the guide to help setup ELBO environment in your local machine.
Good to know: We are just getting started with this service and are actively building it. If you face any problems with the service or API, please reach out to us at [email protected]

Get your API keys

Your API requests are authenticated using API keys. Any request that doesn't include an API key will return an HTTP Authentication error.
Sign up for an account (with a 14 day trial period). You can get the API key from your here at any time on the website.

Setup your Virtual Environment

It's better to run Python in a virtual environment or use conda. To install your virtual environment run:
pip3 install virtualenv virtualenvwrapper
And create an environment using:
virtualenv -p python3 .venv
or if virtualenv is not in path:
~/Library/Python/3.9/bin/virtualenv -p python3 .venv
This creates a virtual Python environment in the .venv folder. To activate this environment use the command:
. .venv/bin/activate
Or the following if you are using the fish shell:
. .venv/bin/activate.fish
If you hit a Command not found error while running virtualenvthen try running virtual env from the user install location. This happens if the package was installed in the user path instead of the system global path.
~/Library/Python/3.9/bin/virtualenv

Install the library

The best way to interact with our API is to use our elbo library. You can install it using the command line below:
Python
pip3 install elbo --upgrade
Good to know: The elbo package still resides in the test pypi repository. We will move it to the official repository once we are out of beta development.

Login to ELBO

Use the command line tool to login.
elbo login
This will prompt you to enter your token. The token can be obtained by logging into the ELBO welcome page.

Make your first task submission

Try out one of the sample ML submission from our examples Github repository. First clone the repository:
git clone https://github.com/elbo-ai/elbo-examples.git
cd elbo-examples/pytorch/mnist_classifier/
Submit the sample task:
elbo run --config elbo.yaml
Here is a sample output of the command that prompts with a list of compute options from our providers:
elbo.client is starting 'Train MNIST Classifier' submission ...
elbo.client Hey Anu 👋, welcome!
elbo.client is uploading sources from ....
elbo.client upload successful.
elbo.client number of compute choices - 28
? Please choose: (Use arrow keys)
» $ 0.0028/hour Micro (for testing) 2 cpu 1Gb mem 0Gb gpu-mem AWS (spot)
$ 0.0150/hour Standard (for testing) 1 cpu 2Gb mem 0Gb gpu-mem Linode (~ 9 mins to provision)
$ 0.0770/hour Micro (for testing) 2 cpu 1Gb mem 0Gb gpu-mem AWS
$ 0.2700/hour Nvidia Tesla K80 4 cpu 61Gb mem 12Gb gpu-mem AWS (spot)
$ 0.6100/hour Nvidia Quadro 4000 16 cpu 32Gb mem 8Gb gpu-mem TensorDock
$ 0.9000/hour Nvidia Tesla K80 4 cpu 61Gb mem 12Gb gpu-mem AWS
$ 0.9180/hour Nvidia V100 8 cpu 61Gb mem 16Gb gpu-mem AWS (spot)
$ 0.9200/hour Nvidia Quadro 5000 2 cpu 4Gb mem 16Gb gpu-mem FluidStack
$ 0.9600/hour Nvidia A5000 2 cpu 16Gb mem 24Gb gpu-mem TensorDock
$ 1.4900/hour Nvidia A4000 12 cpu 64Gb mem 16Gb gpu-mem FluidStack
$ 1.4940/hour Nvidia A40 2 cpu 12Gb mem 48Gb gpu-mem TensorDock
$ 1.5000/hour Nvidia Quadro 6000 8 cpu 32Gb mem 0Gb gpu-mem Linode (~ 9 mins to provision)
$ 1.5140/hour Nvidia A6000 2 cpu 16Gb mem 48Gb gpu-mem TensorDock
$ 2.1600/hour 8x Nvidia Tesla K80 32 cpu 488Gb mem 12Gb gpu-mem AWS (spot)
$ 3.0000/hour 2x Nvidia Quadro 6000 16 cpu 64Gb mem 0Gb gpu-mem Linode (~ 9 mins to provision)
$ 3.0600/hour Nvidia V100 8 cpu 61Gb mem 16Gb gpu-mem AWS
$ 3.6720/hour 4x Nvidia V100 32 cpu 244Gb mem 16Gb gpu-mem AWS (spot)
$ 3.7460/hour 7x Nvidia V100 6 cpu 8Gb mem 16Gb gpu-mem TensorDock
$ 4.3200/hour 16x Nvidia Tesla K80 64 cpu 732Gb mem 12Gb gpu-mem AWS (spot)
$ 4.5000/hour 3x Nvidia Quadro 6000 20 cpu 96Gb mem 0Gb gpu-mem Linode (~ 9 mins to provision)
$ 6.0000/hour 4x Nvidia Quadro 6000 24 cpu 128Gb mem 0Gb gpu-mem Linode (~ 9 mins to provision)
$ 7.3440/hour 8x Nvidia V100 64 cpu 488Gb mem 16Gb gpu-mem AWS (spot)
$ 7.9200/hour 8x Nvidia Tesla K80 32 cpu 488Gb mem 12Gb gpu-mem AWS
$ 9.8318/hour 8x Nvidia A100 96 cpu 1152Gb mem 80Gb gpu-mem AWS (spot)
$13.0360/hour 4x Nvidia V100 32 cpu 244Gb mem 16Gb gpu-mem AWS
$14.4000/hour 16x Nvidia Tesla K80 64 cpu 732Gb mem 12Gb gpu-mem AWS
$24.4800/hour 8x Nvidia V100 64 cpu 488Gb mem 16Gb gpu-mem AWS
$32.7726/hour 8x Nvidia A100 96 cpu 1152Gb mem 80Gb gpu-mem AWS
Thats it! 🥳 Monitor your task progression using elbo show <task_id>.
Good to know: The list of compute options is sorted in the order of best price to performance. Note that the cheapest option may not always be the best nor is the most expensive option.
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On this page
Get your API keys
Setup your Virtual Environment
Install the library
Login to ELBO
Make your first task submission