FedML
auto-split
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| FedML | auto-split | |
|---|---|---|
| 6 | 1 | |
| 4,052 | 12 | |
| 1.8% | - | |
| 9.9 | 0.0 | |
| 6 days ago | over 2 years ago | |
| Python | ||
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
FedML
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[Experiment] The future of AI is open-source, and here is the plan
FedML https://github.com/FedML-AI/FedML might already provide a lot of tools to do the job
- Awesome-Federated-Learning: A curated list of federated learning publications, re-organized from Arxiv (mostly).
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Launch HN: Flower (YC W23) – Train AI models on distributed or sensitive data
This is not new at all. There is a much stronger competitor existing in the market already: FedML (https://fedml.ai). They have a much larger open-source community, and a well-managed and widely-used MLOps (https://open.fedml.ai).
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FedML has just released its completely revamped and redesigned AI Platform and Website.
Website: https://fedml.ai Platform: https://open.fedml.ai/
- FedML AI platform releases the world’s federated learning open platform on the public cloud with an in-depth introduction of products and technologies!
- [Discussion] How feasible is it to partition a DNN model into pieces?
auto-split
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[Discussion] How feasible is it to partition a DNN model into pieces?
Code for https://arxiv.org/abs/2108.13041 found: https://github.com/abanitalebi/auto-split
What are some alternatives?
federated-xgboost - Federated gradient boosted decision tree learning
alpa - Training and serving large-scale neural networks with auto parallelization.
experta - Expert Systems for Python
adaptdl - Resource-adaptive cluster scheduler for deep learning training.
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
MetisFL - The first open Federated Learning framework implemented in C++ and Python.
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
speech-to-text-benchmark - speech to text benchmark framework
openfl - An open framework for Federated Learning.
Federated-Learning-in-PyTorch - Handy PyTorch implementation of Federated Learning (for your painless research)
pfl-research - Simulation framework for accelerating research in Private Federated Learning