Add CABS Merge Method

[zongzhenyang]

Implements CABS (Conflict-Aware and Balanced Sparsification) model merging technique from "CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging".

CABS aims to improve merged model quality by mitigating parameter interference through sequential conflict-aware pruning and applying n:m structural pruning to task vector components.

Key Features:

• Sequential Conflict-Aware Pruning: Processes task vectors in a user-defined pruning_order, masking out parameters already claimed by prior models in the sequence before subsequent pruning. This minimizes destructive overlap.
• N:M Structural Pruning:
  • Applies n:m pruning (retaining n largest magnitude weights out of every m consecutive weights) to the conflict-masked task vector components.
  • n and m values are configurable globally (default_n_val, default_m_val) and per-model (n_val, m_val).
• Weighted Aggregation: Pruned task vectors are scaled by a weight (lambda) and added to the base model.
• Added cabs.py implementing CABSMerge and CABSTask.
• Added CABS example configuration in examples/cabs.yml.

[github-actions]

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[zongzhenyang]

I have read the CLA Document and I hereby sign the CLA

[cg123]

Thanks for the PR! I'd love to have your method in mergekit.

Two things:

• Could you please run the pre-commit hook to format the code and push the changes?
• Would you like to add your method to the table in the README?