Laaj ak tontu

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lu logit bias di soppi?
   • Njortu (logit) ci jeton yiñ tànn balaa ñuy jël misaal
   • Poids de formation model permanent
   • Tàngooru laaj bi yépp
   • Limu jeton yi ci palanteer bi
2. Ci API yu bari, lan la logit bias bu -100 ci kaw benn token mëna def?
   • Dafay tax jeton bi gëna am wërsëg 100 yoon
   • Dafay tere ñu defar token bi
   • efaase token bi ci vocabulaire bi ba fàww
   • Ñaari yoon gaawaayu model bi
3. What numeric range does the documented OpenAI Chat Completions logit_bias accept for a token?
   • From 0 to 1 only
   • From -1 to 1 only
   • From -100 to 100
   • Any string value
4. Logit bias mooy ban ràññeekaay la?
   • Baatu bind bu leer
   • Position frase bi
   • Tur model bi
   • ID jeton numérique
5. Ndax logits yi dañuy jaar ci softmax, lan mooy njeextalu yokk benn bias bu baax?
   • Dafay yokk bu baax diisaayu jeton bi balaa muy normalise
   • Dafay yokk ci anam wu ligneer ab probabilite bu takku
   • Amul benn njariñ ba tàggat
   • Dafay dindi token bi ci xel mi
6. Benn ci njariñ yi gëna mag ci logit bias ci wàllu fine-tuning mooy:
   • Dafay yokk xam-xamu model bi ba fàww
   • Soxlawul ñu tàggataat ko, te mën nañu ko jëfandikoo ci laaj bu nekk
   • Yokk dayo palanteer bi
   • Ci nataal kese lay dox
7. Why should a developer inspect the tokenizer before applying a bias to a visible word?
   • Token IDs are assigned only after sampling
   • Visible words always equal one token
   • The word may be represented by several token IDs, so biasing one ID may not cover all forms
   • The tokenizer controls the model’s training data
8. What is a practical risk of applying a strong positive bias to one token?
   • It increases the context window
   • It changes the model weights permanently
   • It guarantees the token appears exactly once
   • It can distort generation or produce repetitive, awkward text