Consider following assertion and reason pair:
Assertion: A small vocabulary is desirable, as it reduces the size of the embedding matrix. Reason: Decreasing the size of the vocabulary increases the number of tokens in the input.
Assertion and Reason are both true and Reason is a correct explanation of Assertion.
Assertion and Reason are both true and Reason is not a correct explanation of Assertion.
Assertion is true but Reason is false.
Assertion is false but Reason is true.
Consider following statement and mark if it is true or false:
Repeating examples in the pre-training datasets are completely harmless for downstream performance.
TRUE
FALSE
What is the order of the language modeling pipeline?
First, the model, which handles text and returns raw predictions. The tokenizer then makes sense of these predictions and converts them back to text when needed.
First, the tokenizer, which handles text and returns IDs. The model handles these IDs and outputs a prediction, which can be some text.
The tokenizer handles text and returns IDs. The model handles these IDs and outputs a prediction. The tokenizer can then be used once again to convert these predictions back to some text.
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The IIT Madras BS Large Language Models (LLM) Quiz 2 paper sat on 16 Mar 2025, in the January 2025 term: 18 questions for 50 marks in 120 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.
| Feature | LLM Quiz 2 16 Mar 2025 at a glance |
|---|---|
| Term | January 2025 term |
| Subject | Large Language Models |
| Course code | BSDA5004 |
| Questions | 18 |
| Marks | 50 |
| Duration | 120 min |
| MCQ | 5 |
| MSQ | 6 |
| Numerical | 6 |
| Written | 1 |
| Official paper | IIT M DEGREE AN EXAM QDB2 16 Mar 2025 |
| Negative marking | No negative marking. |
| Updated |
