Update README.md

README.md

@@ -1,3 +1,9 @@
+---
+license: mit
+tags:
+- pi
+- mlp
+---
 # pi-predicter
 
 A neural network model that memorizes and predicts digits of π (pi) using Fourier feature encoding. This model demonstrates the memorization capabilities of MLPs with positional encodings by learning to predict specific digits of π at given positions.
@@ -94,7 +100,7 @@ The model uses Fourier features to transform scalar positions into high-dimensio
 - This encoding enables the MLP to learn high-frequency functions of position
 
 ### Memory Efficiency
-Despite memorizing 100,000 digits, the model achieves this with only ~3.5M parameters, demonstrating the efficiency of neural networks as lookup tables for structured data.
+Despite memorizing 100,000 digits, the model achieves this with only ~550k parameters, demonstrating the efficiency of neural networks as lookup tables for structured data.
 
 ## License
 
@@ -102,4 +108,4 @@ This model is released under the MIT License.
 
 ---
 
-**Note**: This model is intended for educational and demonstration purposes, showcasing neural network memorization capabilities rather than mathematical computation. The digits of π are deterministic and can be computed exactly using algorithms; this model demonstrates an alternative approach using machine learning techniques.
+**Note**: This model is intended for educational and demonstration purposes, showcasing neural network memorization capabilities rather than mathematical computation. The digits of π are deterministic and can be computed exactly using algorithms; this model demonstrates an alternative approach using machine learning techniques.