Laajteb KontrolNet

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

1. What does ControlNet add to a pretrained text-to-image diffusion model?
   • A spatial conditioning path that can guide structure using inputs such as edges or pose maps
   • A guarantee that every generated pixel matches the input map exactly
   • A replacement for the text encoder and denoiser
   • A tool that predicts the original training image
2. Lan mooy wareefu 'konvolusioŋ nul' ci ControlNet?
   • Dañuy efaase diisaayu model bi njëkk
   • Dañu tàmbalee ci amul benn poid, kon tàggat yaram dafay tàmbali ci doxalinu model bi njëkk
   • Dañuy soppi nataal yi ci grayscale
   • Dañuy yokk bruit bu bari ci laaj bi
3. Ci yii, yan ci ñoom mooy dugal ControlNet bi baax?
   • Këyitu xayma ay nimero
   • Formu onde audio
   • Yax OpenPose wala kàrtu xóotaayu
   • Xeetu base de done
4. naka la ControlNet di méngoo ak xeetu diffusion bu njëkk bi melni diffusion bu dëgër?
   • Dafay wecci xeetu baas bi yépp
   • Dafay dox rek te amul benn model
   • Dafay dox ci beneen ordinatër ci net bi
   • Dafay takk ni bànxaas buñ mëna tàggat, fekk modelu base bi dafay des ci gelé
5. In a ControlNet workflow, what roles can text and spatial conditioning play?
   • Text can describe semantic/style content while a spatial map supplies structural guidance
   • The spatial map proves the text prompt is factually true
   • Text always supplies exact pixel positions and the map supplies the object name
   • The text prompt is ignored whenever a map is present
6. What training-data scale does the ControlNet paper report as robust for training its controls?
   • Only datasets with exactly 50 examples
   • Both small datasets under 50,000 examples and large datasets over 1 million examples
   • Only datasets larger than 100 million examples
   • No training data is used
7. What does the ControlNet paper report about combining conditioning controls?
   • It permits only one edge map and requires no prompt in every case
   • It accepts text prompts but no spatial controls
   • It tests single or multiple conditions, with or without a text prompt
   • It requires exactly two depth maps for each image
8. Which pretrained part does ControlNet reuse as a strong backbone for learning spatial controls?
   • A database of user prompts
   • A language-model tokenizer only
   • A separately trained classifier for every edge map
   • The deep encoding layers of a pretrained diffusion model