We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！

Characterization of relational table embeddings (VLDB 2024).

ML models + benchmark for tabular data classification and regression

[ICML 2024] BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model

Python CLI tool to refresh schema of Power BI tabular model file (.bim) from Snowflake database

Create measures with TabularEditor using a versatile scripts and XML based templates.

Tool for investigate running Power BI instances as Microsoft Analysis Servises Tabular

This project aims to classify the risk of obesity based on various health and lifestyle factors using an Artificial Neural Network (ANN) implemented in PyTorch. The model is trained on a dataset containing features such as age, dietary habits, physical activity, and more, to predict the obesity risk level.

Successfully established an ANN model which can accurately predict whether a customer will subscribe to term deposits provided by the bank or not.

Dedicated to Machine Learning discipline