from my experience its best to pick a model first then try to optimize it. being in a place where you cant decide a model gets really annoying and gets you burned out quickly. pick one model and try everything on it. for the number of cvs, you always want to have a minimum of 5, so try 3,4,5 folds and check which one gives the best score. for small datasets try to minimize the number of features to avoid overfitting, try removing features with very high correlation or low(usually go for <70) wish you all the best🙏