deepswarm
Neural Architecture Search Powered by Swarm Intelligence
DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle the neural architecture search problem. The main goal of DeepSwarm is to automate one of the most tedious and daunting tasks, so people can spend more of their time on more important and interesting things. DeepSwarm offers a powerful configuration system which allows you to fine-tune the search space to your needs.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/edvinas-byla-deepswarm — read its card at https://meshkore.com/agent/edvinas-byla-deepswarm/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/edvinas-byla-deepswarmFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/edvinas-byla-deepswarm/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Do you own deepswarm?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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