اوپن ویٹ کوئز

جب آپ کوئز دیتے ہیں تو جوابات اور وضاحتیں ظاہر ہوتی ہیں۔

1. OSI تعریف کے تحت 'اوپن ویٹ' ماڈل کو مکمل طور پر اوپن سورس ماڈل سے کیا فرق ہے؟
   • Weights are released, but data, code or open terms may not be
   • There is no meaningful difference between the two terms
   • Open-weights models cannot be downloaded or run by anyone at all
   • Open-source models never release their trained weights
2. A team can download a model checkpoint. What should it check before using the model in a product?
   • Assume downloading grants every commercial and redistribution right
   • The permissions and restrictions in the license for that exact release
   • Rely only on the model family name
   • Treat the download page as a replacement for license terms
3. Why might a downloaded model need more than its weight file for compatible inference?
   • A weight file must include every training example
   • Only the original author can load any model
   • Architecture, tokenizer or preprocessing, configuration and runtime determine how weights are interpreted
   • A model cannot run without a cloud account
4. How can fine-tuning affect a model’s refusal behavior?
   • It guarantees every refusal is preserved
   • It makes the model permanently unable to answer benign requests
   • It remotely updates the original provider’s hosted model
   • It can change refusal behavior, so the adapted model should be reevaluated
5. محققین کے لیے کھلے وزن کا ایک اہم فائدہ کیا ہے؟
   • They can inspect activations and run fine-tuning experiments
   • They receive guaranteed higher scores on every benchmark
   • They no longer need any computing hardware at all
   • They get free access to closed models' training data
6. What should an operator keep when modifying an open-weight model?
   • Only a public download counter
   • A record of modifications and a rollback version
   • A claim that all adaptations are compliant
   • The base model’s marketing slogan
7. Which claim is supported by access to model weights alone?
   • The training data are public
   • The model can be reproduced exactly
   • The parameters can be downloaded under the release’s terms, but other components may still be missing
   • Every use is permitted commercially
8. What should a team check before using a quantized open-weight checkpoint?
   • Only the model family name
   • That quantization guarantees identical quality
   • That the checkpoint needs no tokenizer or runtime
   • Its task behavior and resource use on the intended hardware