---
license: mit
---

# Classifiers Enhanced by Pre-training

This project utilizes a visual encoder from the pre-trained CLIP (ViT-B/32) to build image classifiers. To use the trained models, follow the steps below to set up and run the classifiers.

## Prerequisites

Before you start, make sure you have Python and the necessary libraries installed.

## Download the Trained Models and CIFAR-100 Dataset

You need to download the following trained model weights and CIFAR-100 dataset for running the project:
- `fine-tune-best.pth`: Best model weights after fine-tuning.
- `linear-probe-best.pth`: Best model weights after the linear probe training.
- `train-from-scratch-best.pth`: Best model weights trained from scratch.

Please download these files and place them under the `results/` directory within the project folder.

- `cifar-100-python.tar.gz`: CIFAR-100 dataset.

Please download this file and place it under the `data/` directory within the project folder.


## Installation and Usage

See https://github.com/Gengsheng-Li/Classifiers-enhanced-by-pre-training for more details.