Kontext-Windows-Quiz

Während Sie am Quiz teilnehmen, werden Antworten und Erklärungen angezeigt.

1. Was misst das Kontextfenster eines Modells?
   • Die Bildschirmauflösung der Chat-Oberfläche
   • Die maximale Textmenge in Token, die das Modell auf einmal berücksichtigen kann
   • Wie viele Benutzer können gleichzeitig chatten?
   • Die Gesamtgröße des Trainingsdatensatzes des Modells
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. Das „Lost-in-the-Middle“-Problem bezieht sich auf Modelle, die dazu neigen:
   • Absturz, wenn die Eingabe lang ist
   • Übersetzen Sie die Mitte eines Dokuments in eine andere Sprache
   • Erinnern Sie sich besser an Informationen am Anfang und am Ende einer langen Eingabe als an die Informationen in der Mitte
   • Ignorieren Sie den ersten und letzten Satz vollständig
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