hydra-zen
minimal-ml-template
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hydra-zen | minimal-ml-template | |
---|---|---|
1 | 1 | |
281 | 35 | |
7.1% | - | |
9.4 | 2.0 | |
1 day ago | about 1 year ago | |
Python | Python | |
MIT License | MIT License |
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hydra-zen
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[Project] I built a minimal stateless ML project template built on my current favourite stack
It provides mature configuration support via [Hydra-Zen](https://github.com/mit-ll-responsible-ai/hydra-zen) and automates configuration generation via [decorators](https://github.com/BayesWatch/minimal-ml-template/blob/af387e59472ea67552b4bb8972b39fe95952dd8a/mlproject/decorators.py#L10) implemented in this repo.
minimal-ml-template
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[Project] I built a minimal stateless ML project template built on my current favourite stack
I am here today to share with you all a minimal ml project template that I've recently built, which can be found at https://github.com/AntreasAntoniou/minimal-ml-template/. I became increasingly annoyed at how there weren't any repos out there that provided **stateless** ML project templates, which are absolutely necessary when using kubernetes on spot instances, and I decided to build one. By stateless I mean a repo that by default can store model weights in a remote repo and then download them to continue from where it left off if the previous machine dies. The result was this repository.
What are some alternatives?
kubeproject - A set of tools built to simplify daily driving of cloud resources for individual VM access, Kubernetes batch jobs and miscellaneous useful functionality related to cloud-based ML research
traingenerator - 🧙 A web app to generate template code for machine learning
memorization - Code for "On Memorization in Probabilistic Deep Generative Models"
forward-forward-pytorch - Forward Forward algorithm (by Geoffrey Hinton) implemented with pytorch.
lightning-hydra-template - PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
pytorch-forecasting - Time series forecasting with PyTorch
lightning-flash - Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains