FedML
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, FEDML Nexus AI (https://fedml.ai) is your generative AI platform at scale. (by FedML-AI)
hivemind
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world. (by learning-at-home)
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| FedML | hivemind | |
|---|---|---|
| 6 | 40 | |
| 4,052 | 1,833 | |
| 1.8% | 2.5% | |
| 9.9 | 5.9 | |
| 1 day ago | 21 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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
Posts with mentions or reviews of FedML.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-22.
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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?
hivemind
Posts with mentions or reviews of hivemind.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-03-07.
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You can now train a 70B language model at home
https://github.com/learning-at-home/hivemind is also relevant
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Would anyone be interested in contributing to some group projects?
I really hope you'll join me, for the Petals support, at least! A single docker-compose.yml file is all we need, for now. If we are able to find enough people willing to host some smaller models, perhaps we could expand into the Hivemind, and create our own, custom foundation model one day?
- Hive mind:Train deep learning models on thousands of volunteers across the world
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Could a model not be trained by a decentralized network? Like Seti @ home or kinda-sorta like bitcoin. Petals accomplishes this somewhat, but if raw computer power is the only barrier to open-source I'd be happy to try organizing decentalized computing efforts
Decentralized deep learning: https://github.com/learning-at-home/hivemind
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Orca (built on llama13b) looks like the new sheriff in town
https://github.com/learning-at-home/hivemind - same people behind it, was made before petals I think.
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Do you think that AI research will slow down to a halt because of regulation?
not if we rise to meet that challenge. here's a few tools that facilitate AI research in the face of an advanced persistent threat: Hivemind- a distributed Pytorch framework
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LLM@home
yeah, there's Hivemind. and there's research wrt how to chunk out training workload so it can be scaled up. not sure why there's commentary that latency issues would limit this sort of enterprise, the architecture typically isn't designed for liveness. other subfields of distributed training/inference include zero-knowledge machine learning. besides all of that, there's also adversarial computation like SafetyNets and refereed delegation of computation.
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[D] Google "We Have No Moat, And Neither Does OpenAI": Leaked Internal Google Document Claims Open Source AI Will Outcompete Google and OpenAI
We already have the software for it. There are some projects, but the one I'm most familiar with is https://github.com/learning-at-home/hivemind for training and it's sister project https://petals.ml/ for running large models distributed.
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Run 100B+ language models at home, BitTorrent‑style
I'm not entirely how the approach they're using works [0], but I study federated learning and one of the highly-cited survey papers has several chapters (5 and 6 in particular) addressing potential attacks, failure modes, and bias [1].
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SETI Home Is in Hibernation
The Hivemind project is just that
What are some alternatives?
When comparing FedML and hivemind you can also consider the following projects:
federated-xgboost - Federated gradient boosted decision tree learning
replika-research - Replika.ai Research Papers, Posters, Slides & Datasets
alpa - Training and serving large-scale neural networks with auto parallelization.
GLM-130B - GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
experta - Expert Systems for Python
Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.
adaptdl - Resource-adaptive cluster scheduler for deep learning training.
MetisFL - The first open Federated Learning framework implemented in C++ and Python.
mesh-transformer-jax - Model parallel transformers in JAX and Haiku
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
HiveMind-core - Join the OVOS collective, utils for OpenVoiceOS mesh networking