LLM Tuning: Optimize Your Language Model

I have a question...

The LMM (likely referring to a mass airflow sensor) is housed in a casing through which air flows. If you force more air over the measuring film by using a kind of funnel, wouldn't that increase the performance or improve the readings?

Hello DaBibo!
The conceptual approach isn't bad at all! If you narrow the cross-section to such an extent that the flow velocity in the measurement section is increased by the percentage decrease in the LMM measurement signal, then a compensation effect is achieved.
For nearly incompressible media, such as liquids, the required cross-sectional area can be easily determined using the continuity equation.
In the case of a gas, the laws of gas dynamics must also be taken into account, but I believe that throttling through a moderate reduction in cross-sectional area will likely have a negligible effect.

However, a prerequisite for such compensation would be a uniform decrease in the LMM signal across the entire speed range, i.e., a parallel shift of the characteristic curve.
IMO, with a faulty mass airflow sensor (MAF), the characteristic curve is more likely to be "stepped," meaning that it deviates from the expected curve only above a certain engine speed.
This, at least, is what my measurement from yesterday showed, using my faulty MAF sensor (see the post "MAF sensor statistics"). Please correct me if I'm wrong!

Regards,
Alex.

I once reversed my LMM (likely referring to a Large Language Model) so that the airflow went in the wrong direction.

Subjectively, it performed better.

Hello,

Are there more experiences available regarding incorrectly installed LMMs, especially measurement data?

Best regards, Matthias.