Llama MCQs with answers Page - 4

Here, you will find a collection of MCQ questions on Llama. Go through these questions to enhance your preparation for upcoming examinations and interviews.

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A

Arogya • 2.57K Points
Extraordinary

Q. Which component converts user text into tokens before LLaMA processes it?

  • (A) Compiler
  • (B) Tokenizer
  • (C) Interpreter
  • (D) Debugger

A

Arogya • 2.57K Points
Extraordinary

Q. What is 'temperature' in LLaMA text generation?

  • (A) GPU heat measurement
  • (B) Controls randomness of output
  • (C) Internet speed
  • (D) Training dataset size

A

Arogya • 2.57K Points
Extraordinary

Q. What does 'top-k sampling' control in LLaMA?

  • (A) Number of GPUs
  • (B) Vocabulary filtering during generation
  • (C) Dataset storage
  • (D) Model file format

A

Arogya • 2.57K Points
Extraordinary

Q. Which parameter determines how many tokens LLaMA will generate?

  • (A) batch_size
  • (B) max_tokens
  • (C) learning_rate
  • (D) epochs

A

Arogya • 2.57K Points
Extraordinary

Q. Which of the following is a safety concern with LLaMA models?

  • (A) Slow internet
  • (B) Hallucinated or incorrect information
  • (C) Hard disk failure
  • (D) Screen brightness

A

Arogya • 2.57K Points
Extraordinary

Q. What is a 'system prompt' when using LLaMA?

  • (A) Operating system update
  • (B) Instruction defining model behavior
  • (C) Hardware driver
  • (D) Dataset format

A

Arogya • 2.57K Points
Extraordinary

Q. What does inference mean in LLaMA models?

  • (A) Training the model
  • (B) Using the trained model to generate output
  • (C) Collecting dataset
  • (D) Deleting parameters

A

Arogya • 2.57K Points
Extraordinary

Q. Which Python library is commonly used with LLaMA models?

  • (A) PyTorch
  • (B) Hibernate
  • (C) Laravel
  • (D) Bootstrap

A

Arogya • 2.57K Points
Extraordinary

Q. What is the purpose of embeddings in LLaMA?

  • (A) Store images
  • (B) Represent words as numerical vectors
  • (C) Encrypt passwords
  • (D) Increase GPU fan speed

A

Arogya • 2.57K Points
Extraordinary

Q. Which technique aligns LLaMA responses with human preferences?

  • (A) RLHF
  • (B) Sorting
  • (C) Indexing
  • (D) Compilation

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