use the datasets package to get the datasets

README.md

@@ -48,23 +48,13 @@ The prediction data has a similar structure to the training data and is used for
 Below is an example of how to load and use the datasets using the `datasets` library:
 
 ```python
-import pickle
+from datasets import load_dataset
 
-def load_pickle(file_path):
-    with open(file_path, 'rb') as file:
-        data = pickle.load(file)
-    return data
-
-# Paths to your datasets
-m5_path = 'path/to/m5.pkl'
-police_path = 'path/to/police.pkl'
-prison_path = 'path/to/prison.pkl'
-tourism_path = 'path/to/tourism.pkl'
-
-m5_data = load_pickle(m5_path)
-police_data = load_pickle(police_path)
-prison_data = load_pickle(prison_path)
-tourism_data = load_pickle(tourism_path)
+# Load the datasets from Hugging Face Hub
+m5_data = load_dataset('zaai-ai/hierarchical_time_series_datasets', 'm5')
+police_data = load_dataset('zaai-ai/hierarchical_time_series_datasets', 'police')
+prison_data = load_dataset('zaai-ai/hierarchical_time_series_datasets', 'prison')
+tourism_data = load_dataset('zaai-ai/hierarchical_time_series_datasets', 'tourism')
 
 # Example: Accessing specific data from the datasets
 print("M5 Data:", m5_data)
@@ -73,14 +63,14 @@ print("Prison Data:", prison_data)
 print("Tourism Data:", tourism_data)
 
 # Access the training data
-train_data = prison_data["train"]
+train_data = prison_data['train']
 
 # Access the prediction data
-predict_data = prison_data["predict"]
+predict_data = prison_data['predict']
 
 # Example: Extracting x_values and data
-x_values = train_data["x_values"]
-data = train_data["data"]
+x_values = train_data['x_values']
+data = train_data['data']
 
 print(f"x_values: {x_values}")
 print(f"data shape: {data.shape}")
@@ -88,14 +78,11 @@ print(f"data shape: {data.shape}")
 
 ### Steps to Follow:
 
-1. **Clone the Repository:**
+1. **Install the datasets library:**
    ```sh
-   git clone https://huggingface.co/datasets/zaai-ai/hierarchical_time_series_datasets.git
-   cd hierarchical_time_series_datasets
+   pip install datasets
    ```
-2. **Update the File Paths:**
-   - Ensure the paths to the .pkl files are correct in your Python script.
+2. **Load the Datasets:**
+   - Use the load_dataset function from the datasets library to load the datasets directly from the Hugging Face Hub.
 
-3. **Load the Datasets:**
-   - Use the `pickle` library in Python to load the `.pkl` files.