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moe

moe

Routes Hivemind remote expert and mixture-of-experts workflows, including server setup, custom expert registration, and client-side expert routing.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: moe description: "Routes Hivemind remote expert and mixture-of-experts workflows, including server setup, custom expert registration, and client-side expert routing." disable-model-invocation: true metadata: disco-role: operating license: MIT

Mixture of Experts

Use this route when the task is about hivemind.moe.Server, ModuleBackend, RemoteExpert, RemoteMixtureOfExperts, RemoteSwitchMixtureOfExperts, custom expert registration, or the hivemind-server command.

Include

  • Hosting experts with hivemind.moe.server.Server or background_server.
  • Remote expert clients with RemoteExpert and the MoE routing layers.
  • Declaring and discovering experts with declare_experts and get_experts.
  • Custom expert classes via register_expert_class and custom_module_path.
  • Checkpointing and backend scheduling behavior in ModuleBackend.
  • The hivemind-server console command.

Exclude

  • DHT bootstrap and network reachability debugging; route that to dht.
  • Optimizer wrapping, tensor averaging, and ALBERT training; route those to collaborative-training.
  • Benchmarks and throughput experiments.

Start here

  1. Read references/api-reference.md for the verified server/client signatures.
  2. Read references/workflows.md for the standard server, client, and custom-expert flows.
  3. Read references/troubleshooting.md when the server cannot publish experts, clients cannot find experts, or a custom module fails to load.
  4. Run ../../scripts/check_install.py from the generated skill tree to confirm the installed package and CLI entry points.

What to remember

  • hivemind-server is the package command for serving experts.
  • background_server(...) is the fastest way to spin up a temporary expert host in tests or small demos.
  • client_mode matters when a client can dial out but should not accept inbound connections.
  • custom_module_path lets the server load extra expert definitions from a Python file.
  • Server.create(...) accepts either explicit expert UIDs or generated patterns.
  • On CUDA-capable hosts, the server may default to GPU execution unless you request --device cpu.

Good follow-up questions

  • "How do I host experts and connect to them remotely?"
  • "How do I register a custom expert class?"
  • "How do I fetch experts from the DHT?"
  • "Why does hivemind-server say an expert is missing?"
  • "How do I checkpoint expert state?"
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