Quiz buy soppi mbind

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

1. What kinds of concepts did the original textual-inversion paper personalize?
   • User-provided objects or visual styles
   • Only database schemas
   • Only speech transcripts
   • Only camera calibration parameters
2. Lu tollu ci ñaata misaalu nataal la Textual Inversion di soxla?
   • Benn nataal kese
   • Lu tollu ci 3 ba 5 nataal
   • ay junni nataal
   • Amul benn nataal
3. Lan moo waral fichier yiy soppi bind yi dañu tuuti lool (dañuy faral di nekk ay kilobyte yu néew)?
   • Dañuy kompresse model bi yépp
   • Dañuy bind rek
   • Benn vecteur buñu jàng kese lañuy denc
   • Dañuy joxoñ benn base de done ci net bi
4. Lan moo dul soppeeku ci diiru tàggat yaram ci Inversion Textuelle?
   • misaalu nataal yi
   • Pseudo-baatu bees bi
   • Format biy laaj mbind mi
   • diisaay yi fi nekk ci model bi yépp
5. naka ngay jëfandikoo konsept bi nga jàng ginaaw bi nga soppi bind?
   • Bindal pseudo-word bu bees bi ci benn laaj
   • Taggat model bi saa yu nekk
   • Yeegaat nataal yi
   • Soppi kodu cosaanu model bi
6. Ban perte lañuy jëfandikoo ngir gëna mëna jëfandikoo embedding bu bees bi?
   • A ñakk njubte ci xaaj
   • diffusion denoising perte ci misaalu nataal yi
   • Ñàkka mëna xàmmee kàddu
   • Amul benn ñàkk; tuning manuel la
7. How does textual inversion use the learned token at generation time?
   • It replaces the image decoder
   • It directly edits a generated image without sampling
   • It inserts the token into a text prompt so the frozen text-to-image model can condition on it
   • It changes the model’s tokenizer vocabulary for every user
8. What is a key limitation of a concept learned from only a few example images?
   • It always increases the model’s image resolution
   • It automatically learns every view and lighting condition
   • It changes all existing model concepts equally
   • It may capture incidental features of those examples and generalize imperfectly