openfl
FedML
| openfl | FedML | |
|---|---|---|
| 4 | 6 | |
| 662 | 4,068 | |
| 2.0% | 1.0% | |
| 8.7 | 9.9 | |
| 6 days ago | 6 days ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | 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.
openfl
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Dectralized AI solutions/building blocks?
We have petals.ml for distributing running a single model large model for inference. We have [flower](flower.dev),tensor flow federated,openfl, etc for building federated learning.
- Launch HN: Flower (YC W23) – Train AI models on distributed or sensitive data
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[R][P] OpenFL: An open-source framework for Federated Learning
Code for https://arxiv.org/abs/2105.06413 found: https://github.com/intel/openfl
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?
What are some alternatives?
PySyft - Perform data science on data that remains in someone else's server
federated-xgboost - Federated gradient boosted decision tree learning
FATE - An Industrial Grade Federated Learning Framework
alpa - Training and serving large-scale neural networks with auto parallelization.
fedjax - FedJAX is a JAX-based open source library for Federated Learning simulations that emphasizes ease-of-use in research.
experta - Expert Systems for Python
sparktorch - Train and run Pytorch models on Apache Spark.
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow
adaptdl - Resource-adaptive cluster scheduler for deep learning training.
FindTheMag - A tool to determine optimal projects for Gridcoin crunchers. Maximize your magnitude!
MetisFL - The first open Federated Learning framework implemented in C++ and Python.