basetenlabs

Build a local browser dashboard for digging into AI training rollouts — the text the model actually produced during training. Works on any training output (RL, SFT, DPO, GRPO, eval suites, custom research code, Tinker, prime-rl, verifiers, HuggingFace, anything else) by detecting where the rollouts live and rendering them as a browsable, click-to-read interface. Use this skill whenever the user wants to inspect a training run, debug model outputs, browse generations, see what the model wrote, or "dig into rollouts" — even if they don't say "dashboard". Rollouts are the focus; metrics and configs are secondary context.

Load for any work involving Baseten - deploying/operating models on Dedicated Inference (Truss, custom Docker servers, TRT-LLM engines, Chains), calling hosted Model APIs, running Training jobs (SFT/RL/LoRA), or Model Frontier Gateway.

Guide for adding support for new LLM or VLM models in Megatron-Bridge. Covers bridge, provider, recipe, tests, docs, and examples. Use when the user asks to add, support, onboard, or integrate a new model, or when creating bridges, providers, or recipes for a new model family.