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RyukiRi/Classifiers-Enhanced-by-Pre-training
Classifiers-Enhanced-by-Pre-training is a machine learning model from RyukiRi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
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.
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Updated Apr 16, 2024
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From the Hugging Face model README
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.
Before you start, make sure you have Python and the necessary libraries installed.
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.
See https://github.com/Gengsheng-Li/Classifiers-enhanced-by-pre-training for more details.