# Fine-tuning Details
"facebook/dino-vitb16" # pre-trained model from which to fine-tune

"Graphcore/vit-base-ipu" # config specific to the IPU (Used POD4)

Using: [https://github.com/graphcore/Gradient-HuggingFace/tree/main/image-classification](https://github.com/graphcore/Gradient-HuggingFace/commit/826b72cba150be52e7420a3440a31e3096b73c78)

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)