mixture-of-experts VS tutel

Compare mixture-of-experts vs tutel and see what are their differences.

mixture-of-experts

PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538 (by davidmrau)
moe mixture-of-experts sparsely-gated-mixture-of-experts Pytorch re-implementation
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tutel

Tutel MoE: An Optimized Mixture-of-Experts Implementation (by microsoft)
Pytorch moe mixture-of-experts NLP Transformer
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mixture-of-experts tutel
2 1
835 658
- 3.0%
5.3 6.5
16 days ago 16 days ago
Python Python
GNU General Public License v3.0 only MIT License
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mixture-of-experts

Posts with mentions or reviews of mixture-of-experts. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-20.
  • [Rumor] Potential GPT-4 architecture description
    2 projects | /r/LocalLLaMA | 20 Jun 2023
  • Local and Global loss
    1 project | /r/pytorch | 4 Mar 2021
    I have a requirement of training pipeline similar to Mixture of Experts (https://github.com/davidmrau/mixture-of-experts/blob/master/moe.py) but I want to train the Experts on a local loss for 1 epoch before predicting outputs from them (which would then be concatenated for the global loss of MoE). Can anyone suggest what’s the best way to set up this training pipeline?

tutel

Posts with mentions or reviews of tutel. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing mixture-of-experts and tutel you can also consider the following projects:

pytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers

hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

mmdetection - OpenMMLab Detection Toolbox and Benchmark

ModuleFormer - ModuleFormer is a MoE-based architecture that includes two different types of experts: stick-breaking attention heads and feedforward experts. We released a collection of ModuleFormer-based Language Models (MoLM) ranging in scale from 4 billion to 8 billion parameters.

yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time

mixture-of-experts vs pytorch-tutorial tutel vs hivemind mixture-of-experts vs transformers tutel vs transformers mixture-of-experts vs mmdetection tutel vs ModuleFormer mixture-of-experts vs hivemind mixture-of-experts vs yolov5 mixture-of-experts vs Real-Time-Voice-Cloning mixture-of-experts vs ModuleFormer