3 boosters for "fine-tuning" — AI-graded, open source, ready to install
A skill for fine-tuning and training language models on Hugging Face's cloud GPU infrastructure using TRL, supporting SFT, DPO, GRPO methods and GGUF conversion for local deployment. Developers and ML engineers working with cloud-based model training benefit from this comprehensive guidance.
A Cursor-integrated coding standards and linting configuration toolkit for NeMo Curator projects, helping teams enforce consistent data processing code quality with Ruff-based rules and exceptions.
A practical guide to Supervised Fine-Tuning using SFTTrainer and Unsloth optimizations, enabling developers to efficiently adapt pre-trained LLMs for instruction-following with 2x faster training. Ideal for ML engineers building custom instruction-tuned models and reasoning systems.
