from what i understand the “preview” models are quite handicapped, usually the benchmark is the full fat model for that reason. the recent openAI one (they have stupid names idk what is what anymore) had a similar problem.
If it’s not a preview model, it’s possible a bigger model would help, but usually prompt engineering is going to be more useful. AI is really quick to get confused sometimes.
the distilled models are a little goofier, it’s possible that might influence it, since they tend to behave weirdly sometimes, but it depends on the model and the application.
AI is still fairly goofy unfortunately, it’ll take time for it to become omniscient.
from what i understand the “preview” models are quite handicapped, usually the benchmark is the full fat model for that reason. the recent openAI one (they have stupid names idk what is what anymore) had a similar problem.
If it’s not a preview model, it’s possible a bigger model would help, but usually prompt engineering is going to be more useful. AI is really quick to get confused sometimes.
It might be, idk, my coworker set it up. It’s definitely a distilled model though. I did hope it would do a better job on such a small input though.
the distilled models are a little goofier, it’s possible that might influence it, since they tend to behave weirdly sometimes, but it depends on the model and the application.
AI is still fairly goofy unfortunately, it’ll take time for it to become omniscient.