These are Fine-Tuning questions of the kind Wipro actually asks — the patterns that keep coming back in Wipro's AI project interviews, where what matters is applying Fine-Tuning sensibly for clients rather than research depth. Treat this page as a mock interview: say every answer out loud before revealing it. If one surprises you, the lesson behind it is linked at the bottom.
Wipro Fine-Tuning concept questions
What is catastrophic forgetting, and how would you catch it?
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What is quantization, and how much GPU memory would a 7B model need?
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Wipro Fine-Tuning applied & hands-on questions
A fine-tuned model launched last week. The task eval score went from 87% to 93%, but the support team says customers are complaining more. Give your diagnosis and your immediate action.
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How to use this page: Wipro rarely asks something you've never seen — they ask a standard Fine-Tuning concept and then push one level deeper ("why?", "what would you do if..."). Master the concept in the Fine-Tuning course lessons, and the follow-up stops being scary.
Keep practising: When to Fine-Tune, LoRA & PEFT, Evaluating LLMs and LLMOps & Monitoring cover what most Wipro Fine-Tuning rounds test — and the Wipro exam guide covers the rest of their selection process.