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SkillsMP has collected 4 skills from tenstorrent/tt-inference-server. Open a skill to review its source and details.
Showing 4 of 4 collected skills.
Checklist for adding or modifying code in the workflow engine (run_workflows.py plus the llm_module/report_module/test_module/workflow_module packages) — new models, workflows, media runners, spec tests, report kinds, or CLI flags — and wiring it back to the…
Checklist for onboarding a new LLM to the cpp_server inference backend so it serves through Dynamo — registering the model type, fetching tokenizer files, tokenizer static data (eos/stop/think tokens), and Dynamo discovery (reasoning + tool-call parsers,…
Capture on-CPU and off-CPU flamegraphs of the running tt_media_server_cpp main (Drogon) and worker processes using Linux perf + Brendan Gregg's FlameGraph. Use when the user asks to profile the C++ server, find a performance bottleneck, identify slow code…
Trigger Tenstorrent Blaze media server and tt-metal upstream Docker image builds with gh. Use when the user asks to build Blaze and Metal Docker images, run the tt-shield media server image workflow, or build tt-metal images from the tt-llm-engine submodule…