Update README.md

README.md

@@ -166,3 +166,71 @@ configs:
   - split: bppq
     path: agronomic_visual_cognition/bppq-*
 ---
+
+
+# 🥬 CABBAGE: Comprehensive Agricultural Benchmark Backed by AI-Guided Evaluation
+
+[**🌐 Homepage**](https://huggingface.co/datasets/boilnserve/cabbage) | [**🏆 Leaderboard**](https://huggingface.co/datasets/boilnserve/cabbage) | [**🤗 Dataset**](https://huggingface.co/datasets/boilnserve/cabbage) | [**💻 GitHub**](https://github.com/boilnserve/cabbage)
+
+## Table of Contents
+- [CABBAGE: Comprehensive Agricultural Benchmark Backed by AI-Guided Evaluation](#%F0%9F%A5%AC-cabbage-comprehensive-agricultural-benchmark-backed-by-ai-guided-evaluation)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#benchmark-tracks-and-subsets)
+      - [🖼️ Agronomic Visual Cognition](#%F0%9F%96%BC%EF%B8%8F-agronomic-visual-cognition)
+      - [📚 Agricultural Scientific Knowledge](#%F0%9F%93%9A-agricultural-scientific-knowledge)
+      - [🛠️ Agricultural Procedural Reasoning](#%F0%9F%9B%A0%EF%B8%8F-agricultural-procedural-reasoning)
+    - [Loading the Dataset](#loading-the-dataset)
+
+## Dataset Description
+
+- **Homepage:** https://huggingface.co/datasets/boilnserve/cabbage
+- **Repository:** https://github.com/boilnserve/cabbage
+- **Paper:** Not yet published
+- **Leaderboard:** https://huggingface.co/datasets/boilnserve/cabbage
+- **Size of downloaded dataset files:** 3.74 GB
+- **Size of the auto-converted Parquet files:** 240.84 MB
+- **Number of rows:** 74,206
+
+**CABBAGE** is a large-scale, multimodal benchmark for evaluating AI systems in agriculture across three complementary task macro-categories: **Visual Cognition**, **Scientific Knowledge**, and **Procedural Reasoning**. Each macro-category contains high-quality, domain-specific subsets built from curated or expert-reviewed sources.  
+
+## Benchmark Tracks and Subsets
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/6824cf491019386a26b831c1/PYEaWom37vSKPDfKqt7fo.png" width="600"/>
+
+### 🖼️ Agronomic Visual Cognition
+Evaluates image-based plant understanding and visual QA.
+
+- **`eppo`**: Plant pest and disease image classification (from EPPO data)
+- **`plantnet`**: Species-level classification using Pl@ntNet imagery
+- **`bppq`**: The Big Plant Pathology Quiz — visual QA for pathology
+
+### 📚 Agricultural Scientific Knowledge
+Tests scientific factual knowledge, retrieval, and reasoning over structured agronomic data.
+
+- **`agriexam`**: Multiple-choice exams from official agricultural education materials
+- **`cca_ceu`**:  Multiple-choice questions from the Certified Crop Adviser datasets and Continuing Education Unit materials
+- **`embrapa`**: Questions derived from Brazilian Agricultural Research Corporation technical guide series
+
+### 🛠️ Agricultural Procedural Reasoning
+Challenges models on procedural tasks derived from domain-relevant manuals and wikiHow entries.
+
+- **`wikihow_arrange`**: Arrange steps of an agricultural procedure in the correct order
+- **`wikihow_missing`**: Identify missing steps in an agricultural workflow
+- **`wikihow_next`**: Predict the next step in a given task
+- **`wikihow_all`**: Generate the full sequence of steps required to carry out an agricultural task
+
+## Loading the Dataset
+
+You can load any specific configuration and split using the Hugging Face `datasets` library:
+
+```python
+from datasets import load_dataset
+
+# Example: Load all the splits from the Agronomic Visual Cognition subset
+dataset_dict = load_dataset("boilnserve/cabbage", name="agronomic_visual_cognition")
+
+# Example: Load the Embrapa split from the Agricultural Scientific Knowledge subset
+dataset = load_dataset("boilnserve/cabbage", name="agricultural_scientific_knowledge", split="embrapa")
+```