# Fine-tuning Details
# 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)

Using: [image_classification-dinov2-base.ipynb](https://huggingface.co/internetoftim/dinov2-base-eurosat/blob/main/image_classification-dinov2-base.ipynb)

Run the notebook in Gradient, make sure to upload the .ipynb file from this repository:
[![Run on Gradient](https://assets.paperspace.io/img/gradient-badge.svg)](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"))


[![Ask for help in GC Slack ](https://img.shields.io/badge/Slack-Join%20Graphcore's%20Community-blue?style=flat-square&logo=slack)](https://www.graphcore.ai/join-community)

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