AWS published detailed guidelines on fine-tuning OpenAI’s gpt-oss-120B and 20B models using SageMaker AI and Hugging Face’s TRL framework. The tutorial highlights efficient strategies including LoRA (low-rank adaptation), MXFP4 (4-bit quantization), and distributed training with Hugging Face Accelerate and DeepSpeed ZeRO-3 for scalable performance.
These approaches help manage compute and memory costs without sacrificing model accuracy.
SageMaker’s managed infrastructure, along with built-in tools for experiment tracking, model governance, and secure deployment, makes it enterprise-ready for production-grade LLM customization.
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