timm_parameters: Model Configuration Overview

timm_parameters is a comprehensive collection of the number of parameters for all deep learning models available in the timm (PyTorch Image Models) library.

Included Files

• timm_model_parameter_counts.csv
  A CSV file listing all supported models in timm along with their corresponding parameter counts, in the ascending order of parameter counts.

• timm_parameters.ipynb
  A Jupyter notebook containing the code used to generate the CSV file.
  It extracts model metadata such as architecture names, parameter counts, and other configuration details.

Use Cases

This repository can be useful for:

• Quickly comparing model sizes
• Selecting appropriate models based on resource constraints
• Working with models having comparable parameters

Feel free to explore, contribute, or use this resource to streamline your model evaluation process!