Tag: llm fine-tuning

A practical MLX-first recipe for experimenting with openai/gpt-oss-20b on a 64GB Apple Silicon Mac without confusing local LoRA work for CUDA-scale training.

Why Apple Silicon is useful for local LLM prototyping and LoRA experiments, but still has sharp boundaries compared with CUDA-scale NeMo or Hugging Face training.

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.

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.