Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Kediska Windows Context

Dib u eeg miisaaniyada guud ee calaamada, qoondaynta wax soo galinta iyo soo saarista, xadka qiimaynta wakhtiga dheer, dib u soo celinta ganacsiga, iyo habdhaqanka marka codsigu dhaafo awooda.

Wadooyinka haga ee la xidhiidhaMacnaha Daaqadaha
Su'aal 1 ee 8

Muxuu cabbirayaa daaqadda macnaha guud ee moodeelka?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Muxuu cabbirayaa daaqadda macnaha guud ee moodeelka?
    • xallinta shaashadda ee interface chat
    • Qadarka ugu badan ee qoraalka, calaamadaha, moodeelku wuxuu tixgelin karaa hal mar
    • Immisa isticmaale ayaa isla sheekeysan kara
    • Wadarta guud ee qaabka xogta cabbirka tababarka
  2. How should a token be interpreted when budgeting language-model context?
    • As exactly one full word in every language
    • As exactly one sentence in every tokenizer
    • As a tokenizer-defined unit whose relation to words depends on the model and text
    • As the API password used to send a request
  3. In a decoder-style request with a shared input-and-continuation budget, which supplied material uses that budget?
    • Instructions, conversation turns, document tokens, and the generated continuation
    • Only the latest user message
    • Only stored application files that were never supplied
    • Only generated output, with input always free
  4. Under a dense full-attention pairwise-interaction model, how does comparison count scale when a request's token length doubles?
    • It becomes only twice as large under that model
    • It stays unchanged regardless of length
    • It becomes half as large
    • It becomes four times as large under the quadratic model
  5. Dhibaatada 'dhexda ka luntay' waxaa loola jeedaa moodooyinka u janjeera:
    • Shil mar kasta oo gelintaadu dheeraato
    • Utarjum barta dhexe ee dukumeentiga luqad kale
    • Xusuusnow macluumaadka bilowga iyo dhammaadka gelinta dheer si ka fiican tan dhexe
    • Iska daa jumladaha ugu horreeya iyo kuwa ugu dambeeya gebi ahaanba
  6. Why can retrieval be combined with a language model's limited context window?
    • It guarantees the lowest total cost for every workflow
    • It selects passages to supply rather than requiring the whole knowledge base as input
    • It permanently increases the model's supported token capacity
    • It removes the need to evaluate generated answers
  7. In an illustrative shared context budget of 8,000 tokens, input uses 6,500. How many tokens remain before other limits or overhead?
    • 6,500
    • 8,000
    • 14,500
    • 1,500
  8. What can happen when an input exceeds a language model interface's supported context?
    • Rejection, truncation, or application-side shortening, depending on the setup
    • Automatic permanent memory of all excluded text
    • Guaranteed silent deletion of the oldest message in every system
    • Automatic expansion of every model's trained architecture