TIES: Eliminating redundancy and disagreements

Introduced in this paper by Yadav et al., TIES-Merging is designed to efficiently merge multiple task-specific models into a single multitask model.

A typical script will look like so:

models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: OpenPipe/mistral-ft-optimized-1218
    parameters:
      density: 0.5
      weight: 0.5
  - model: mlabonne/NeuralHermes-2.5-Mistral-7B
    parameters:
      density: 0.5
      weight: 0.3
merge_method: ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  normalize: true
dtype: float16