add 1st model card description and necessary files for following updates

README.md

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 license: apache-2.0
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+# TabM Model Instructions
+
+## Model Overview
+
+### 1.1 Method Description
+This implementation utilizes the approach from the research paper:  
+**"TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling" (ICLR 2025)**
+
+- **Paper Link**: https://arxiv.org/abs/2410.24210
+- **Original Repository**: https://github.com/yandex-research/tabm
+
+### 1.2 Motivation
+Compared to traditional machine learning methods used in NeoRanking, we aim to explore the performance of Tabular Deep Learning approaches on this type of data for classification tasks.
+
+## Training Details
+
+### 2.1 Training Data
+The detailed training dataset is located at: `data/tabm_train.tsv`
+
+### 2.2 Training Parameters
+- Model parameters were optimized using the `hyper` framework for parameter tuning
+- Training script: `src/tabm_train.py`
+- Testing script: `src/tabm_test.py`
+
+### 2.3 Testing Data
+- Test dataset: `data/tabm_test.tsv`
+- Evaluation metrics have been updated in `spaces/leaderboard`
+
+## Model Usage
+
+### 3.1 Installation
+```bash
+pip3 install tabm
+```
+
+### 3.2 Training
+```bash
+bash scripts/tabm_train.sh
+```
+
+### 3.3 Testing
+```bash
+bash scripts/tabm_test.sh
+```
+
+## Special Notes
+
+Our use of TabM fully complies with the **Apache-2.0 license**. If you need to reference or reuse this model, please adhere to the original author's citation requirements and properly attribute the source.