PM KArcher (Mergekit)

KArcher Concept: Computes the Karcher mean (also known as the Riemannian barycenter or Fréchet mean) of the input model parameters. This provides a geometrically sound way to average points on a manifold, which is suitable for model weights. Use Cases: Finding a "central" or "average" model among a set of diverse models in a way that respects the geometry of the weight space More robust averaging than simple linear averaging, especially for models far apart in weight space Inputs: Takes 2 or more models. No base_model is used. Key Parameters: max_iter (global): Maximum iterations for the Karcher mean algorithm. Default 10 tol (global): Convergence tolerance. Default 0.5