Upload README.md with huggingface_hub

README.md

@@ -11,10 +11,19 @@ tags:
 - graph-neural-networks
 - surrogate-modeling
 pretty_name: Nesting Tasks Dataset for 2D Nesting Efficiency Estimation
-dataset_info:
-  splits:
-  - name: train
-    num_examples: 100000
+configs:
+- config_name: tasks
+  data_files:
+  - tasks.parquet
+- config_name: parts
+  data_files:
+  - parts.parquet
+- config_name: shapes
+  data_files:
+  - shapes.parquet
+- config_name: constraints
+  data_files:
+  - constraints.parquet
 ---
 
 # Nesting Tasks Dataset for 2D Nesting Efficiency Estimation
@@ -127,6 +136,22 @@ print(f"   🟡 Validation instances : {len(val_df)}")
 print(f"   🔴 Test instances       : {len(test_df)}")
 ```
 
+### Loading Directly from Hugging Face Hub
+
+You can also download or stream these relational tables directly from the Hugging Face Hub using their specific dataset configuration names:
+
+```python
+from datasets import load_dataset
+
+# Load individual tables using configuration subsets
+tasks_ds = load_dataset("clallier/nesting-tasks-2d", name="tasks")
+parts_ds = load_dataset("clallier/nesting-tasks-2d", name="parts")
+shapes_ds = load_dataset("clallier/nesting-tasks-2d", name="shapes")
+constraints_ds = load_dataset("clallier/nesting-tasks-2d", name="constraints")
+
+print(tasks_ds)
+```
+
 ---
 
 ## 🛠️ Handling Missing Values (Nulls)