Update README.md

README.md

@@ -10,6 +10,28 @@ The AlphaNum dataset, curated by Louis Rädisch, is a comprehensive collection o
 
 Images derived from the MNIST dataset have been color inverted to maintain consistency with the rest of the data. Vision Transformer Models have been fine-tuned to harmonize the data from diverse sources, enhancing the dataset's accuracy. For instance, the 'A-Z handwritten alphabets' dataset originally did not differentiate between upper and lower case letters, an issue rectified in this new compilation.
 
+
+## Sources:
+1) [Handwriting Characters Database](https://github.com/sueiras/handwritting_characters_database) 
+2) [MNIST](https://huggingface.co/datasets/mnist)
+3) [AZ Handwritten Alphabets in CSV format](https://www.kaggle.com/datasets/sachinpatel21/az-handwritten-alphabets-in-csv-format)
+
+The dataset files have been scaled down to 24x24 pixels and recolored from white-on-black to black-on-white to ensure uniformity.
+
+## Dataset Structure
+### Data Instances
+A single data instance in this dataset comprises an image of a handwritten character or digit, accompanied by its corresponding ASCII label.
+
+### Data Fields
+1) 'image': This field contains the image of the handwritten character or digit.
+2) 'label': This field provides the ASCII label corresponding to the character or digit in the image.
+
+### Data Splits
+The dataset is bifurcated into training and test subsets to facilitate the building and evaluation of models.
+
+## Dataset Use
+The AlphaNum dataset is apt for tasks associated with text recognition, document processing, and machine learning. It is particularly beneficial for constructing, fine-tuning, and enhancing OCR models.
+
 ## ASCII Table
 | ASCII Value | Character |
 |-------------|-----------|
@@ -106,25 +128,4 @@ Images derived from the MNIST dataset have been color inverted to maintain consi
 | 124         | \|        |
 | 125         | }         |
 | 126         | ~         |
-| 999         | null      |
-
-## Sources:
-1) [Handwriting Characters Database](https://github.com/sueiras/handwritting_characters_database) 
-2) [MNIST](https://huggingface.co/datasets/mnist)
-3) [AZ Handwritten Alphabets in CSV format](https://www.kaggle.com/datasets/sachinpatel21/az-handwritten-alphabets-in-csv-format)
-
-The dataset files have been scaled down to 24x24 pixels and recolored from white-on-black to black-on-white to ensure uniformity.
-
-## Dataset Structure
-### Data Instances
-A single data instance in this dataset comprises an image of a handwritten character or digit, accompanied by its corresponding ASCII label.
-
-### Data Fields
-1) 'image': This field contains the image of the handwritten character or digit.
-2) 'label': This field provides the ASCII label corresponding to the character or digit in the image.
-
-### Data Splits
-The dataset is bifurcated into training and test subsets to facilitate the building and evaluation of models.
-
-## Dataset Use
-The AlphaNum dataset is apt for tasks associated with text recognition, document processing, and machine learning. It is particularly beneficial for constructing, fine-tuning, and enhancing OCR models.
+| 999         | null      |