Intel® End-to-End AI Optimization Kit release v1.2

Highlights

This release introduces 3 new capabilities: RecDP-AutoFE, RecDP-LLM and DeltaTuner.

• RecDP-AutoFE provides automatic feature engineering capability to generate new features for any tabular dataset, this function is proven to be able to achieve competitive or even better accuracy comparing to data scientist's solution.
• RecDP-LLM is an one stop solution for LLM data preparation, it provides a ray and spark enhanced parallel data pipeline for pretrain data clean, RAG text extract/splitting/indexing, and finetune data quality evaluation and enhancement.
• DeltaTuner is an extension for Peft to improve LLM fine-tuning speed through multiple optimizations, including leveraging the compact model constructor denas to construct/modify the compact delta layers in a hardware-aware and train-free approach and adding more new deltatuning algorithms.

This release provides following major features:

• RecDP-AutoFE
• RecDP-LLM
• DeltaTuner

Papers and Blogs

• Enhance Productivity with Auto Feature Engineering Workflow

Versions and Components

• PyTorch >= 1.13.1
• Python 3.10
• Peft 0.4.0
• Pypark 3.4.1
• Ray 2.7.1

Links

• https://github.com/intel/e2eAIOK
• https://pypi.org/project/e2eAIOK-deltatuner/1.2.0/
• https://pypi.org/project/e2eAIOK-recdp/1.2.0/

Full Changelog: https://github.com/intel/e2eAIOK/commits/v1.2