nimbo
nimbo-examples
nimbo | nimbo-examples | |
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5 | 2 | |
123 | 0 | |
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8.8 | 0.0 | |
over 2 years ago | almost 3 years ago | |
Python | Python | |
GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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nimbo
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Show HN: SpotML – Managed ML Training on Cheap AWS/GCP Spot Instances
You should really mention / give attribution / emphasize more that this is a fork of https://spotty.cloud and you took a lot from https://github.com/nimbo-sh/nimbo as well.
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Show HN: Nimbo – Run jobs (and notebooks) on AWS with a single command
Hey everyone,
I (Miguel) am an ML PhD from the University of Edinburgh and Juozas is a Software Engineer also from Edinburgh.
Together we developed Nimbo, a dead-simple CLI that wraps the AWS CLI, allowing you to run code on AWS as if you were running it locally. You can find the source code here (https://github.com/nimbo-sh/nimbo) and the docs here (https://docs.nimbo.sh).
We decided to build this because we were frustrated with how cumbersome using AWS was, and we just wanted to be able to run jobs on AWS as easily as we run them locally. At the same time, we wanted to make use of the cheap spot instances (on Nimbo, this is a single parameter). All in all, we didn't like the current user experience of working with AWS, and we believed it was possible to vastly improve it.
For this reason, we also provide many useful commands to make it faster and easier to work with AWS, such as launching notebooks on EC2, easily checking prices, logging onto an instance, or syncing data to/from S3 (you can see some useful commands at https://docs.nimbo.sh/useful-commands).
Unlike other similar services, we are solely client-side, meaning that the code runs on your EC2 instances and data is stored in your S3 buckets (we don't have a server; all the infrastructure orchestration happens in the Nimbo package). We are also open contribution, meaning that all the source code is publicly available on our GitHub, and we welcome community contribution.
We have tons of ideas for Nimbo, like adding docker support, and providing instances with preloaded datasets like ImageNet, so that you don't have to download and store it yourself - you simply spin the instance, and the dataset is available at /datasets. We are currently working on adding GCP support, so that you can use AWS or GCP with the same config file.
We are happy to receive any feedback and suggestions you have.
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[P] Nimbo: Run jobs on AWS with a single command
My friend and I just launched Nimbo, a dead-simple CLI that wraps AWS CLI, allowing you to run code on AWS as if you were running it locally. GitHub: https://github.com/nimbo-sh/nimbo. Docs: https://docs.nimbo.sh.
nimbo-examples
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[P] Nimbo: Run jobs on AWS with a single command
Also, to map pip to conda you simply have to put the pip packages under the "- pip:" section in the conda file. Check for example our Detection example conda file with pip installed Detectron and opencv: https://github.com/nimbo-sh/nimbo-examples/blob/main/detectron/env.yml
What are some alternatives?
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
criu-image-streamer - Enables streaming of images to and from CRIU during checkpoint/restore with low overhead
dbt-spark - dbt-spark contains all of the code enabling dbt to work with Apache Spark and Databricks