nemo-mbridge-recipe-recommenderlisted

# Auto Recipe — Recipe Index & Recommendation This skill indexes every shipped recipe and helps users pick the right starting config, adjust parallelism, and avoid common pitfalls. ## How to Use This Skill 1. Ask the user for: **model name/size**, **GPU count & type**, **training goal** (pretrain / SFT / PEFT), and **sequence length** (if non-default). 2. Look up the best-match recipe in the index below. 3. Recommend the recipe function name + entry-point command. 4. Provide adjustment advice (parallelism resizing, batch tuning, pitfalls). ## First Answer Checklist When recommending recipes, always include these distinctions before the long index details: 1. **Library recipes** under `src/megatron/bridge/recipes/` are for functional training and use `scripts/training/run_recipe.py`. 2. **Performance recipes** under `scripts/performance/` are for upper-bound throughput benchmarks. They use mock data and should not be presented as production training recipes. 3. For a first-time Bridge smoke test, recommend `llama3_8b_sft_config` with mock data via `--dataset llm-pretrain-mock`. Do not use `llm-finetune` for the setup-only tryout unless the user specifically asks for an SFT data path. 4. For normal SFT recommendations, use `--dataset llm-finetune`; for pretrain and mock validation recommendations, use `--dataset llm-pretrain-mock`. 5. After the recipe and dataset, give the required resizing rules: TP must divide `num_key_value_heads`, keep TP withi