Update README.md

README.md

@@ -300,6 +300,39 @@ task_categories:
 
 JSONSchemaBench is a benchmark of **real-world JSON schemas** designed to evaluate **structured output generation** for Large Language Models (LLMs). It contains approximately **10,000 JSON schemas**, capturing diverse constraints and complexities.
 
+## 📢 Important Update (March 10th, 2025)
+
+We have restructured the dataset to include train/val/test splits. If you downloaded the dataset before this date, you might encounter errors like `KeyError: 'Github_easy'`.
+
+To fix this issue, please follow one of the options below:
+
+1. Update How Subsets Are Accessed:
+If you previously used:
+
+```python
+from datasets import load_dataset, concatenate_datasets, DatasetDict, Dataset
+
+subset: DatasetDict = load_dataset("epfl-dlab/JSONSchemaBench")
+subset["Github_easy"]
+```
+You can update it to:
+
+```python
+from datasets import load_dataset, concatenate_datasets, DatasetDict, Dataset
+
+subset: DatasetDict = load_dataset("epfl-dlab/JSONSchemaBench", name="Github_easy")
+subset: Dataset = concatenate_datasets([subset["train"], subset["val"], subset["test"]])
+```
+
+2. Load the Dataset in the Old Structure:
+If you need the previous structure, you can use a specific revision:
+
+```python
+dataset = load_dataset("epfl-dlab/JSONSchemaBench", revision="e2ee5fdba65657c60d3a24b321172eb7141f8d73")
+```
+
+We apologize for the inconvenience and appreciate your understanding! 😊
+
 ## 📌 Dataset Overview
 - **Purpose:** Evaluate the **efficiency** and **coverage** of structured output generation.
 - **Sources:** GitHub, Kubernetes, API specifications, curated collections.