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---
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.
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