Rama contributed to the keras-io repository by addressing a bug related to the reporting of trainable parameter counts in the TabTransformer tutorial. Focusing on both the baseline and TabTransformer configurations, Rama corrected discrepancies between the documented and actual parameter counts, ensuring that the reported model complexity accurately reflects the underlying implementation. This work involved updating Python code and Jupyter notebooks, as well as revising Markdown documentation to align with the corrected values. By improving the accuracy of resource estimation for developers and learners, Rama demonstrated attention to detail and a methodical approach to code correction and technical documentation within the project.