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1Z0-1127-25 Fundamentals of Large Language Models Practice Question

A development team wants to generate code snippets from natural language. Which model strategy should they adopt?

⚠ Common exam trap

Oracle often tests the distinction between general-purpose and domain-specific models, and the trap here is that candidates assume any large language model can handle code generation equally well, overlooking the critical fine-tuning on code corpora that makes Code Llama superior for this task.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Use a code-specific model like Code Llama.

Code Llama is a specialized variant of Llama 2 that has been fine-tuned on code datasets, enabling it to generate syntactically and semantically correct code from natural language prompts. This makes it the optimal choice for code generation tasks, as general-purpose LLMs lack the targeted training on code structures and programming languages.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
Use a code-specific model like Code Llama.
Why this is correct
Correct: Code-specific models are fine-tuned for code generation.
✗
Use a general-purpose LLM like Llama 2.
Why it's wrong here
Incorrect: General models are less optimized for code.
✗
Use a multimodal model.
Why it's wrong here
Incorrect: Multimodal models handle images and text, not code-specific.
✗
Use an embedding model for text.
Why it's wrong here
Incorrect: Embedding models are for similarity, not generation.

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1Z0-1127-25 Fundamentals of Large Language Models Practice Question

Why each option matters

Option-by-option breakdown

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