Unlock the potential of finetuning Large Language Models (LLMs). Learn from industry expert, and discover when to apply finetuning, data preparation techniques, and how to effectively train and evaluate LLMs.

An Open-Source Python framework for Locally Weighted Regression and Classification, built on PyTorch and Scikit-Learn

We propose a flexible conditional modeling framework that learns structured dependencies between variables by blending linear and nonlinear transformations.

This architecture enables recursive knowledge extraction and transfer across tasks. By structuring learning feedback in layers, it optimizes generalization and accelerates adaptive model development. 本アーキテクチャは、タスク間における再帰的な知識抽出と転移を可能にします。学習フィードバックを階層構造で整理することで、汎化性能を高め、適応的なモデル構築を加速します。