Deploying Fine-Tuned Models Quiz
Quiz covering Fine-Tuning Language Models
Deploying Fine-Tuned Models Quiz
5 questions | Pass: 70% | Earn 25 points
Questions in this quiz
A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.
- 1
Which of the following is the most common reason to perform fine-tuning on a pre-trained language model?
- 2
When deploying a fine-tuned model, what is the primary benefit of using Parameter-Efficient Fine-Tuning (PEFT) techniques like LoRA?
- 3
You have fine-tuned a model for a customer support chatbot. After deployment, the model exhibits 'catastrophic forgetting.' What is the most likely cause?
- 4
When serving a fine-tuned model in a production environment, why is 'Quantization' often applied?
- 5
You are evaluating a fine-tuned model using a test set. You notice that the training loss is decreasing, but the performance on your specific domain evaluation task is plateauing. What is the most effective technical step to diagnose or fix this?
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