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Awesome GitHub RepositoriesInterpolation Parameter Optimization
Algorithms for calculating the optimal weighting ratios for blending multiple model parameter sets.
Distinct from Weight Interpolation: Focuses on the optimization of the blending ratios themselves rather than the act of interpolating weights
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Awesome Interpolation Parameter Optimization GitHub Repositories
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- arcee-ai/mergekit
arcee-ai/mergekit
7,156在 GitHub 上查看MergeKit is a toolkit for combining multiple pre-trained large language models into a single entity using algorithmic blending. It provides a specialized system for parameter interpolation and weight extraction to unify model capabilities. The project distinguishes itself through an evolutionary merge optimizer that tunes parameters based on quantitative evaluation metrics. It also features a mixture of experts orchestrator capable of converting dense models into sparse architectures and a tokenizer alignment tool for transplanting embeddings between different models. The toolkit covers a br
Calculates optimized weights for linear interpolation based on the geometric similarity between models.
Pythonllamallmmodel-merging
