README.md

---
title: README
emoji: 📈
colorFrom: red
colorTo: blue
sdk: static
pinned: false
---

[![Neuralk-AI](https://cdn-images.welcometothejungle.com/v82GguLLmnQoPY4v0Gu9ZTGrzAwtFaKjAd0pF-mNsFw/resize:auto:400::/czM6Ly93dHRqLXByb2R1Y3Rpb24vYWNjb3VudHMvdXBsb2Fkcy9vcmdhbml6YXRpb25zL2xvZ29zL2E5MWQ5M2U5MWMyNDYyZjA0MzNjMTc0Zjc0YjNjMjMwLzU2NmZkOTBjLTY2M2ItNDJlZC04N2I4LTVmMGIwYTg1NGU0NS5wbmc)](https://neuralk-ai.com)

# 🌍 Join Neuralk-AI's tabular AI ecosystem!

[![GitHub stars](https://img.shields.io/github/stars/Neuralk-AI/TabBench?style=for-the-badge&logo=github&logoColor=white&color=45b69c)](https://github.com/Neuralk-AI/TabBench)
[![LinkedIn](https://img.shields.io/badge/LinkedIn-2d7d6b?style=for-the-badge&logo=linkedin&logoColor=2d7d6b)](https://www.linkedin.com/company/neuralk-ai) 
[![Twitter](https://img.shields.io/badge/Twitter-1c6354?style=for-the-badge&logo=twitter&logoColor=1c6354)](https://twitter.com/neuralk_ai) 
[![Blog](https://img.shields.io/badge/Blog-68dec4?style=for-the-badge&logo=internet&logoColor=68dec4)](https://neuralk-ai.com/blog)
[![Careers](https://img.shields.io/badge/Careers-135748?style=for-the-badge&logo=internet&logoColor=135748)](https://neuralk-ai.com/careers)

---

# 💡 Bringing tabular models closer to industrial tasks

Neuralk-AI builds the first Tabular Foundational Model focused on industrial tasks, starting with Commerce. 

We created **TabBench**, the first benchmark dedicated to evaluating and advancing tabular models on real-world use cases and ML workflows typical in industries like Commerce, such as product categorization, deduplication, and more.

**What TabBench currently supports (frequently updated!):**  
  - Real-world use cases: product categorization, deduplication
  - Easily evaluate your model or dataset for each use case thanks to a steamlined Workflow logic (load → vectorize → predict → evaluate)  
  - Evaluation on both industrial datasets (private) & academic ones (OpenML)
  - Classical ML & Tabular Foundation models: NICL, TabICL, TabPFNv2, XGBoost, CatBoost, LightGBM, MLP  
  - Built on **Neuralk Foundry**, an open-source, modular framework to customize your own industrial workflows 

---
 
# 🚀 How to get started?

Install TabBench with pip:

```bash
pip install tabbench
```

or directly clone the repository:

```bash
git clone https://github.com/Neuralk-AI/TabBench
cd TabBench
```

Jump straight into our example notebooks to start exploring tabular models on industrial tasks:

| File | Description                                             |
----------|---------------------------------------------------------|
| [1 - Getting Started with TabBench](https://github.com/Neuralk-AI/TabBench/blob/main/tutorials/1%20-%20Getting%20Started%20with%20TabBench.ipynb)    | Discover how TabBench works and train your first tabular model on a Product Categorization task.
| [2 - Adding a local or internet dataset](https://github.com/Neuralk-AI/TabBench/blob/main/tutorials/2%20-%20Adding%20a%20local%20or%20internet%20dataset.ipynb) | How to add your own datasets for evaluation (local, downloadable, or OpenML).
| [3 - Use a custom model](https://github.com/Neuralk-AI/TabBench/blob/main/tutorials/3%20-%20Use%20a%20custom%20model.ipynb) |  How to integrate a new model in TabBench and use it on different use cases.

---

For more information about TabBench, open-source code and tutorials, you can check our [Github Page](https://github.com/Neuralk-AI/TabBench/)

---