update md

README.md

@@ -1,29 +1,29 @@
-<<<<<<< HEAD
----
-license: mit
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-=======
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+--- 
+language: 
+- eng
+- lang2
+pretty_name: "LiTraj"
 tags:
 - uMLIPs
 - chemistry
 - DFT
 - GNN
+- structure-to-property
+license: "MIT"
 ---
 
-
 ![toc](https://github.com/AIRI-Institute/LiTraj/raw/main/figures/toc.png)
 
 ### LiTraj: A Dataset for Benchmarking Machine Learning Models for Predicting Lithium Ion Migration
-![License](https://img.shields.io/badge/License-MIT-darkred.svg)
+
 [![GitHub](https://img.shields.io/badge/-Github-181717?logo=github&logoColor=white)](https://github.com/AIRI-Institute/LiTraj)
 [![Custom Badge Text](https://img.shields.io/badge/MACE_uMLIP_benchmark_example-Colab_Notebook-orange?logo=googlecolab&color=orange)](https://colab.research.google.com/drive/1vkF8doorp58hKE0a_W2kVOAMWHPGOjzd#sandboxMode=true&scrollTo=s1TnrzPzoyDb)
+![License](https://img.shields.io/badge/License-MIT-darkred.svg)
 
 
 This repository contains links to datasets for benchmarking machine learning models for predicting Li-ion migration, as described in our paper ["Benchmarking machine learning models for predicting lithium ion migration"](https://www.nature.com/articles/s41524-025-01571-z), along with the description of Python utilities for handling the datasets.
 
 
-
 ## Contents
 - [About](#about)
 - [Source links](#available-datasets-and-source-links)
@@ -314,4 +314,3 @@ If you use the LiTraj dataset, please, consider citing our paper
 	doi = {10.1038/s41524-025-01571-z}
 }
 ```
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