NVIDIA/Megatron-Bridge/adding-model-support A
Guide for adding support for new LLM or VLM models in Megatron-Bridge.
Recommend and customize Megatron Bridge recipes for a user's model, GPU count, and training goal.
Install this skill (Claude Code)
# Clone and copy the skill into your project
git clone https://github.com/NVIDIA/skills.git
mkdir -p .claude/skills
cp -r skills/skills/Megatron-Bridge/recipe-recommender .claude/skills/
# Or for personal use: ~/.claude/skills/Transparent heuristic — same formula for every entry. Total 85/100.
Guide for adding support for new LLM or VLM models in Megatron-Bridge.
Dev environment setup for Megatron Bridge — container-based development, uv package management, lockfile regeneration, adding dependencies, Slurm container usage, and common build...
Bump a pinned dependency (TransformerEngine, Megatron-LM, NRX, etc.), regenerate the lockfile, open a PR, and drive it to green by attaching a watchdog to the "CICD NeMo" workflow...
CI/CD reference for Megatron Bridge — pipeline structure, commit and PR workflow, CI failure investigation, and common failure patterns.
Code style and quality rules for Megatron Bridge — ruff configuration, naming conventions, type hints, mypy rules, docstrings, copyright headers, logging, and the code review check...
Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data.