Update README.md

README.md

@@ -15,21 +15,21 @@ The original dataset, Fineweb-Edu-Fortified, is a deduplicated version of the Fi
 The original dataset is detailed in its dataset card here.
 Dataset Composition
 
-    Score: Represents the quality of the text content.
-    Text: The main content of the webpage (limited to the first 512 tokens).
-    URL: The source URL from which the text was extracted.
+Score: Represents the quality of the text content.
+Text: The main content of the webpage (limited to the first 512 tokens).
+URL: The source URL from which the text was extracted.
 
 Use Cases
 
 This filtered version has several potential use cases, including:
 
-    Model Healing: Can be used as fine-tuning data for restoring or enhancing model knowledge after Depth Up scaling or model pruning. The high-quality, curated educational content ensures that pruned models can recover key domain knowledge effectively.
+Model Healing: Can be used as fine-tuning data for restoring or enhancing model knowledge after Depth Up scaling or model pruning. The high-quality, curated educational content ensures that pruned models can recover key domain knowledge effectively.
 
-    Synthetic Dataset Creation: The dataset can be used in a pipeline to generate question-answer pairs by extracting sections of the text, generating relevant questions, and providing the answers. This makes it useful for data augmentation and Q&A models.
+Synthetic Dataset Creation: The dataset can be used in a pipeline to generate question-answer pairs by extracting sections of the text, generating relevant questions, and providing the answers. This makes it useful for data augmentation and Q&A models.
 
-    Smaller Dataset Training: It can be employed for training smaller LLMs by utilizing the filtered high-quality educational text, especially useful in cases where resource constraints exist.
+Smaller Dataset Training: It can be employed for training smaller LLMs by utilizing the filtered high-quality educational text, especially useful in cases where resource constraints exist.
 
-    Topic-Based Fine-Tuning: The dataset can be grouped by subject or topic based on the content of the text or URL, allowing for the creation of more specialized training datasets tailored to particular domains or educational levels.
+Topic-Based Fine-Tuning: The dataset can be grouped by subject or topic based on the content of the text or URL, allowing for the creation of more specialized training datasets tailored to particular domains or educational levels.
 
 License
 
@@ -38,7 +38,7 @@ Citation
 
 If you use this dataset, please cite the original dataset:
 
-ruby
+
 
 @dataset{airtrain2024finewebedu,
   title={Fineweb-Edu-Fortified},