Update README.md

README.md

@@ -18,7 +18,7 @@ Clone the following repositories:
 git clone https://github.com/CYF2000127/MolNexTR
 ```
 ### Example usage of the model
-1. First create and activate a [conda](https://numdifftools.readthedocs.io/en/stable/how-to/create_virtual_env_with_conda.html) environment with the following command in a Linux environment
+1. First create and activate a [conda](https://numdifftools.readthedocs.io/en/stable/how-to/create_virtual_env_with_conda.html) environment with the following command in a Linux environment:
 ```
 conda create -n molnextr python=3.8
 conda activate molnextr
@@ -28,15 +28,15 @@ conda activate molnextr
 ```
 pip install -r requirements.txt
 ```
-Alternatively, use the following command
+Alternatively, use the following command:
 ```
 conda env create -f environment.yml
 ```
 
 
-2. Download the model checkpoint from our [Hugging Face Repo](https://huggingface.co/datasets/CYF200127/MolNexTR/blob/main/molnextr_best.pth) or Zenodo Repo: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.13304899.svg)](https://doi.org/10.5281/zenodo.13304899) and put in your own path 
+3. Download the model checkpoint from our [Hugging Face Repo](https://huggingface.co/datasets/CYF200127/MolNexTR/blob/main/molnextr_best.pth) or Zenodo Repo: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.13304899.svg)](https://doi.org/10.5281/zenodo.13304899) and put in your own path 
 
-3. Run the following code to predict molecular images:
+4. Run the following code to predict molecular images:
 ```python
 import torch
 from MolNexTR import molnextr