quiz.json

{
  "lesson": "30-bpe-tokenizer-from-scratch",
  "title": "BPE Tokenizer From Scratch",
  "questions": [
    {
      "stage": "pre",
      "question": "Why does a byte-level BPE tokenizer start from a 256-symbol alphabet?",
      "options": [
        "It guarantees any UTF-8 input can be represented before any merge is learned",
        "It is the smallest alphabet that supports the English language",
        "It matches the GPU warp size on most accelerators",
        "It removes the need to store a merge table"
      ],
      "correct": 0,
      "explanation": "The 256 raw byte ids cover every possible UTF-8 input. No unknown token is ever required because any input can be expressed as a sequence of bytes."
    },
    {
      "stage": "check",
      "question": "What does each BPE training step do?",
      "options": [
        "Splits a random word and assigns it a new id",
        "Counts adjacent symbol pairs across the corpus and merges the most frequent one",
        "Decreases the vocabulary by removing the least common id",
        "Trains a small neural network to score subwords"
      ],
      "correct": 1,
      "explanation": "Each step finds the highest-frequency adjacent pair across the corpus, merges it into a new symbol, and records the merge."
    },
    {
      "stage": "check",
      "question": "When encoding new text, in what order are merges applied?",
      "options": [
        "In random order until none apply",
        "By position in the input, left to right, regardless of training rank",
        "By the rank the merge received during training, lowest rank first",
        "By the bytes of the pair, sorted alphabetically"
      ],
      "correct": 2,
      "explanation": "Inference applies merges in the order they were learned. The earliest merge in the table wins when multiple merges could apply."
    },
    {
      "stage": "check",
      "question": "What is the encoder's behavior on a special-token string when allow_special is False?",
      "options": [
        "It raises an error",
        "It maps the string to its reserved id",
        "It encodes the literal bytes of the string",
        "It silently skips the string"
      ],
      "correct": 2,
      "explanation": "With allow_special off, a string like <|endoftext|> is treated as raw bytes and goes through the merge loop like any other input."
    },
    {
      "stage": "post",
      "question": "Why does the decoder never need an unknown-token id?",
      "options": [
        "Every learned token is the concatenation of two known tokens, recursing down to single bytes",
        "The encoder strips unknown tokens before decoding",
        "The model rejects unknown ids during sampling",
        "The decoder always returns the empty string for unknown ids"
      ],
      "correct": 0,
      "explanation": "Every id resolves either to a raw byte or to two previously known ids. Recursive expansion always terminates in bytes, which decode to UTF-8."
    },
    {
      "stage": "post",
      "question": "What happens to the encoded length of a fixed sentence as the target vocabulary grows?",
      "options": [
        "It increases linearly with the vocabulary size",
        "It stays constant because each id encodes a single byte",
        "It tends to decrease because larger vocabularies cover more subwords",
        "It oscillates randomly because BPE is non-deterministic"
      ],
      "correct": 2,
      "explanation": "Larger vocabularies learn more merges, so common subwords collapse into single ids and the encoded sequence gets shorter."
    }
  ]
}