remote-gpu-trainer
An Agent Skill for the DL experiment lifecycle: RUN (a GPU you own or rent) → VERIFY the number is real → DELIVER reproducible, single-source figures and tables.
An Agent Skill for the whole life of a DL experiment — RUN a job (on a GPU you own or rent), VERIFY that the number is real, and DELIVER it as organized, single-source, reproducible figures and tables. Its deepest part is still remote-GPU operations (AutoDL, RunPod, vast.ai, Lambda, Paperspace, the Chinese platforms 恒源云 / 矩池云 / Featurize / 揽睿星舟, bare SSH, Slurm, Kubernetes — one instance or a fan-out of many), now wrapped in the full run → verify → deliver arc.
⚡ 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/hanyuyuan6-remote-gpu-trainer — read its card at https://meshkore.com/agent/hanyuyuan6-remote-gpu-trainer/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/hanyuyuan6-remote-gpu-trainerFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/hanyuyuan6-remote-gpu-trainer/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own remote-gpu-trainer?
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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