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Exam NCA-GENL Topic 10 Question 29 Discussion

Actual exam question for NVIDIA's NCA-GENL exam
Question #: 29
Topic #: 10
You are in need of customizing your LLM via prompt engineering, prompt learning, or parameter-efficient fine-tuning. Which framework helps you with all of these?

Suggested Answer: D Vote an answer

The NVIDIA NeMo framework is designed to support the development and customization of large language models (LLMs), including techniques like prompt engineering, prompt learning (e.g., prompt tuning), and parameter-efficient fine-tuning (e.g., LoRA), as emphasized in NVIDIA's Generative AI and LLMs course.
NeMo provides modular tools and pre-trained models that facilitate these customization methods, allowing users to adapt LLMs for specific tasks efficiently. Option A, TensorRT, is incorrect, as it focuses on inference optimization, not model customization. Option B, DALI, is a data loading library for computer vision, not LLMs. Option C, Triton, is an inference server, not a framework for LLM customization. The course notes:
"NVIDIA NeMo supports LLM customization through prompt engineering, prompt learning, and parameter- efficient fine-tuning, enabling flexible adaptation for NLP tasks." References: NVIDIA Building Transformer-Based Natural Language Processing Applications course; NVIDIA NeMo Framework User Guide.

by Ian at Aug 30, 2025, 04:12 AM

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