Fine-Tuning Tutorials
Fine-Tuning Tutorials
Use the tutorials in this section to gain a deeper understanding of how the NVIDIA NeMo Customizer microservice enables fine-tuning tasks.
Tutorials are organized by complexity and typically build on one another. The tutorials reference NMP_BASE_URL, which is the base URL of your NeMo Platform deployment. Refer to the Setup guide for installation, setup, and platform URL guidance.
Getting Started
Dataset Preparation
Learn how to format datasets for different model types.
datasets chat-models completion-modelsPackage native-v1, wheels-v1, and adapter-wheels-v1 environment FileSets for GRPO.
Customization Jobs
Learn how to perform supervised fine-tuning with LoRA adapters using custom data.
nemo-customizerLearn how to perform supervised fine-tuning using custom data by modifying all training parameters.
nemo-customizerLearn how to run a DPO customization job with preference pairs on the RL backend.
nemo-customizer dpoLearn how to compress a larger teacher model into a smaller student model using knowledge distillation.
nemo-customizer knowledge-distillationMine hard negatives from NVIDIA’s published NVDocs dataset, fine-tune Nemotron 3 Embed 1B, then deploy Retriever NIM and compare nDCG and Recall against the base model.
embedding-models bi-encoder nemo-customizerRegister an existing triplet dataset as a fileset and train on it instead of mined NVDocs data.
embedding-models datasets nemo-customizer