Context Windows Test

Răspunsurile și explicațiile apar pe măsură ce susțineți testul.

1. Ce măsoară fereastra de context a unui model?
   • Rezoluția ecranului interfeței de chat
   • Cantitatea maximă de text, în jetoane, pe care modelul o poate lua în considerare deodată
   • Câți utilizatori pot conversa prin chat în același timp
   • Dimensiunea totală a setului de date de antrenament al modelului
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. Problema „pierdut în mijloc” se referă la modelele care tind să:
   • Se blochează ori de câte ori intrarea este lungă
   • Traduceți mijlocul unui document într-o altă limbă
   • Amintiți informațiile de la începutul și de la sfârșitul unei intrări lungi mai bine decât la mijloc
   • Ignorați în întregime prima și ultima propoziție
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