| # To fine-tuning Details | |
| [nielsr/dinov2-base](https://huggingface.co/nielsr/dinov2-base) # pre-trained model from which to fine-tune | |
| [Graphcore/vit-base-ipu](https://huggingface.co/Graphcore/vit-base-ipu_) # config specific to the IPU (Used POD4) | |
| How to use in IPU: [https://huggingface.co/internetoftim/dinov2-base/blob/main/image_classification-dinov2-base.ipynb](https://huggingface.co/internetoftim/dinov2-base/blob/main/image_classification-dinov2-base.ipynb) | |
| Run the notebooks in this repository: | |
| [](https://ipu.dev/3YOs4Js) | |
| Poplar SDK: v3.2.1 | |
| Dataset: | |
| load a custom dataset from local/remote files or folders using the ImageFolder feature | |
| option 1: local/remote files (supporting the following formats: tar, gzip, zip, xz, rar, zstd) | |
| url = "https://madm.dfki.de/files/sentinel/EuroSAT.zip" | |
| files = list(Path(dataset_dir).rglob("EuroSAT.zip")) | |
| [](https://www.graphcore.ai/join-community) |