Add pipeline tag and improve model card

This PR adds the `image-classification` pipeline tag to the model metadata to improve its discoverability on the Hugging Face Hub. It also refines the model card structure by adding links to the paper, project page, and GitHub repository, along with a brief description of the MozzaVID dataset.

README.md

@@ -1,42 +1,47 @@
 ---
-license: mit
 datasets:
 - PaPieta/MozzaVID_Small
 - PaPieta/MozzaVID_Base
 - PaPieta/MozzaVID_Large
+license: mit
+pipeline_tag: image-classification
 tags:
-  - volumetric
-  - 3D
-  - X-ray_tomography
-  - mozzarella
-  - cheese
-  - food_science
+- volumetric
+- 3D
+- X-ray_tomography
+- mozzarella
+- cheese
+- food_science
 ---
 
-# MozzaVID dataset - evaluated models checkpoints
+# MozzaVID: Mozzarella Volumetric Image Dataset
 
-Checkpoints of models evaluated on the MozzaVID dataset in the associated article. 
+This repository contains model checkpoints evaluated on the **MozzaVID** dataset, as presented in the paper "[MozzaVID: Mozzarella Volumetric Image Dataset](https://huggingface.co/papers/2412.04880)".
 
-### [[Paper](https://arxiv.org/abs/2412.04880)] [[Project website](https://papieta.github.io/MozzaVID/)]
+MozzaVID is a large, clean, and versatile volumetric classification dataset containing X-ray computed tomography (CT) images of mozzarella microstructure. It enables the classification of 25 cheese types and 149 cheese samples across three different resolutions.
 
-For details on model use, visit our [GitHub](https://github.com/PaPieta/MozzaVID).
+- **Paper:** [arXiv:2412.04880](https://arxiv.org/abs/2412.04880)
+- **Project Website:** [MozzaVID Project Page](https://papieta.github.io/MozzaVID/)
+- **Repository:** [GitHub - PaPieta/MozzaVID](https://github.com/PaPieta/MozzaVID)
 
 ## Data
 
-Hugging Face - WebDataset format:
-
+The dataset is available on Hugging Face in WebDataset format:
 * [Small split](https://huggingface.co/datasets/PaPieta/MozzaVID_Small)
 * [Base split](https://huggingface.co/datasets/PaPieta/MozzaVID_Base)
 * [Large split](https://huggingface.co/datasets/PaPieta/MozzaVID_Large)
 
-Raw data: [[LINK](https://archive.compute.dtu.dk/files/public/projects/MozzaVID/)].
+Raw data can also be accessed via the [DTU archive](https://archive.compute.dtu.dk/files/public/projects/MozzaVID/).
+
+## Usage
 
+For details on model training and evaluation, please visit the [official GitHub repository](https://github.com/PaPieta/MozzaVID). The repository provides scripts such as `evaluate_model.py` and `train_model.py` to work with these checkpoints.
 
 ## Citation
 
-If you use the dataset or models in your work, please consider citing our publication:
+If you use the dataset or models in your work, please consider citing the following publication:
 
-```
+```bibtex
 @misc{pieta2024b,
   title={MozzaVID: Mozzarella Volumetric Image Dataset},
   author={Pawel Tomasz Pieta and Peter Winkel Rasmussen and Anders Bjorholm Dahl and Jeppe Revall Frisvad and Siavash Arjomand Bigdeli and Carsten Gundlach and Anders Nymark Christensen},
@@ -47,4 +52,4 @@ If you use the dataset or models in your work, please consider citing our public
   primaryClass={cs.CV},
   url={https://arxiv.org/abs/2412.04880},
 }
-```
+```