Mattral/Composed-Mixture-of-Experts-Engine

moe-engine is a research-grade infrastructure layer for training large Mixture-of-Experts language models at hyperscale. It is designed around one core constraint: at 10K+ GPUs, nodes die continuously. The system must keep training alive end-to-end — routing correctly, checkpointing durably, and resuming without operator intervention.

GitHub repository with 10 stars and 8 forks.

Language: Python

Topics: distributed-training, fault-tolerance, llm-training, machine-learning, mixture-of-experts, moe, production-infrastructure, pytorch, sparse-training, triton

Open provider repository

24h trend summary

Trending score 0.61, freshness score 0.92, stars gained +0, forks gained +0.

Latest metric snapshot

2026-06-15: 10 stars and 8 forks.

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