add loading

README.md

@@ -29,6 +29,8 @@ size_categories:
   - [Social Impact of Dataset](#social-impact)
   - [Discussion of Biases](#biases)
   - [Other Known Limitations](#limitations)
+- [Data Loading](#data-loading)
+
 
 
 <a name="dataset-description"></a>
@@ -137,3 +139,31 @@ The WikiHowQA dataset is derived from WikiHow, a community-driven platform. Whil
 <a name="limitations"></a>
 ### Other Known Limitations
 The dataset only contains 'how-to' questions and their answers. Therefore, it may not be suitable for tasks that require understanding of other types of questions (e.g., why, what, when, who, etc.). Additionally, while the dataset contains a large number of instances, there may still be topics or types of questions that are underrepresented.
+
+<a name="data-loading"></a>
+## Data Loading
+
+There are two primary ways to load the main dataset part:
+
+1. Directly from the file (if you have the .jsonl file locally, you can load the dataset using the following Python code):
+
+```python
+import json
+
+dataset = []
+with open('wikiHowNFQA.jsonl') as f:
+    for l in f:
+        dataset.append(json.loads(l))
+```
+
+This will result in a list of dictionaries, each representing a single instance in the dataset.
+
+2. From the Hugging Face Datasets Hub:
+
+If the dataset is hosted on the Hugging Face Datasets Hub, you can load it directly using the datasets library:
+
+```python
+from datasets import load_dataset
+dataset = load_dataset('wikiHowNFQA')
+```
+This will return a DatasetDict object, which is a dictionary-like object that maps split names (e.g., 'train', 'validation', 'test') to Dataset objects. You can access a specific split like so: dataset['train'].