Tag: nemo

Why LLM fine-tuning projects fail when teams jump to NeMo or Hugging Face training commands before deciding the model, data, evaluation, serving, and governance loop.

Outcome: Defined a fine-tuning operating loop that connects base-model choice, data curation, PEFT, evaluation, distributed training, serving, and governance into one repeatable release path.

A practical map of NVIDIA NeMo for teams that want to curate data, fine-tune open-source LLMs, evaluate them, and move from research checkpoints to production inference.

Outcome: Separated data curation, fine-tuning, alignment, evaluation, export, and serving concerns so open-source LLM customization could move from experiments to governed production workflows.