Continuation of issue #2474 as discussed here

Add default parameters for all projection heads

It's helpful to know what the default parameters were in the papers to get started. We should add the default projection head parameters which were used for pre-training on Imagenet to all projection and prediction heads in lightly/models/modules/heads.py.

We should update the prediction_agent when calling LabelModel.predict. Add a parameter to the LabelModel.predict method, that defines the prediction_agent, by default this parameter should be a generic name of the label model implementation.

When computing the isosurface, when 4 simplex edges crosses the isosurface, we add 2 triangles to the isosurface triangulation.

Right now we add these arbitrarily (in these 3 lines) but we should add them so that the curvature is minimized.

The current state o

In simulation mode, when I try to run a single simulation using the nn-2-layer classifier and sbert feature extraction method, it gives me this error

ValueError: Error: method 'nn2layer' is not implemented for entry point asreview.models.classifiers.

However, using this combination of classification and feature extraction method in a simulation-batch does not give me the same error. Using th