tutel VS ModuleFormer

Compare tutel vs ModuleFormer and see what are their differences.

tutel

Tutel MoE: An Optimized Mixture-of-Experts Implementation (by microsoft)

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. (by IBM)
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tutel ModuleFormer
1 1
658 216
3.0% 4.6%
6.5 5.7
16 days ago 25 days ago
Python Python
MIT License Apache License 2.0
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.
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tutel

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

ModuleFormer

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

What are some alternatives?

When comparing tutel and ModuleFormer you can also consider the following projects:

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

LMOps - General technology for enabling AI capabilities w/ LLMs and MLLMs

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

StableLM - StableLM: Stability AI Language Models

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

lingvo - Lingvo

lm-scorer - 📃Language Model based sentences scoring library