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Kuis Pengkodean Pasangan Byte
Tinjau penggabungan BPE, simbol awal, cakupan byte, asal kompresi, pengkodean peringkat, potongan kata langka, aritmatika kosakata, dan decoding UTF-8.
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Which adjacent-symbol operation is repeated in common BPE vocabulary training?
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- Which adjacent-symbol operation is repeated in common BPE vocabulary training?
- Deleting all low-frequency words from the language
- Merging a most-frequent pair into a larger symbol
- Sorting complete documents by title
- Selecting pairs solely by their alphabetical spelling
- Seperti apa BPE memperlakukan teks tersebut ketika memulai pelatihan?
- Seluruh kalimat
- Memperbaiki blok 8 token
- Karakter atau byte individual
- Frasa yang sudah diterjemahkan sebelumnya
- In a byte-level BPE configuration covering all 256 base byte values, how can unfamiliar valid UTF-8 text be represented?
- Through its constituent bytes when larger pieces are unavailable
- By storing every possible complete word in the finite vocabulary
- By requiring the input to be translated into English first
- By assigning every unseen character one shared unknown ID
- Dari manakah algoritma BPE berasal sebelum NLP mengadopsinya?
- Kompresi gambar
- Pengodean audio
- Pengindeksan basis data
- Kompresi data
- When GPT-2's published BPE encoder finds multiple eligible adjacent pairs, what determines its merge choice?
- A new random vocabulary fit on that one input
- The text file's creation date
- The priorities in the learned merge ranks
- The order of a human-written list of target meanings
- What can happen when an unfamiliar word lacks larger learned BPE pieces?
- It must be replaced by an unrelated synonym
- It remains represented by several smaller available pieces
- It necessarily becomes one new learned token during inference
- It is always silently removed from the input
- An illustrative BPE vocabulary has 256 base byte tokens, two distinct added merge tokens, and one separate special token. What is its total size?
- 256
- 258
- 512
- 259
- In GPT-2's published decoder, what is reconstructed before converting the result from UTF-8 into text?
- The complete byte sequence represented by the token pieces
- An independent Unicode character from every individual token first
- A new corpus-frequency table for training merges
- The model's output-label probabilities