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<a align="center" href="" target="_blank">
<img
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src="https://media.roboflow.com/open-source/autodistill/autodistill-banner.png"
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# Autodistill ViT Module
This repository contains the code supporting the ViT target model for use with [Autodistill](https://github.com/autodistill/autodistill).
[ViT](https://huggingface.co/google/vit-base-patch16-224-in21k) is a classification model pre-trained on ImageNet-21k, developed by Google. You can train ViT classification models using Autodistill.
Read the full [Autodistill documentation](https://autodistill.github.io/autodistill/).
Read the [ViT Autodistill documentation](https://autodistill.github.io/autodistill/target_models/vit/).
## Installation
To use the ViT target model, you will need to install the following dependency:
```bash
pip3 install autodistill-vit
```
## Quickstart
```python
from autodistill_vit import ViT
target_model = ViT()
# train a model from a classification folder structure
target_model.train("./context_images_labeled/", epochs=200)
# run inference on the new model
pred = target_model.predict("./context_images_labeled/train/images/dog-7.jpg", conf=0.01)
```
## License
The code in this repository is licensed under an [Apache 2.0 license](LICENSE).
## 🏆 Contributing
We love your input! Please see the core Autodistill [contributing guide](https://github.com/autodistill/autodistill/blob/main/CONTRIBUTING.md) to get started. Thank you 🙏 to all our contributors!
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