Updating ReadMe

README.md

@@ -72,60 +72,12 @@ Step 2 : Create the *npz.tar.gz files
 
 Refer to the directory structure section below to understand how these files have been staged inside huggingface.
 
-**Data Preparation**
-
-Please refer to our [github](https://github.com/baskargroup/mpfbench-tools/tree/master/DataPrep) page that provides codes for doing data preparation for SciML models:
-
-```
-https://github.com/baskargroup/mpfbench-tools/tree/master/DataPrep
-```
-
 **License**
 ```
 CC-BY-NC-SA-4.0
 ```
 
-**How to download files from Huggingface**
-
-To run the example code, you need to install the following package:
-
-```bash
-pip install huggingface_hub
-```
-
-The following script demonstrates how to download a directory from the Hugging Face Hub:
-
-```python 
-from huggingface_hub import HfApi, hf_hub_download
-import os
-import shutil
-
-REPO_ID = "BGLab/mpf-bench"
-DIRECTORY = "2Dbubble/bubbleGroup1_npz"
-
-# Initialize the Hugging Face API
-api = HfApi()
-
-# List files in the directory
-files_list = api.list_repo_files(repo_id=REPO_ID, repo_type="dataset")
-
-# Filter the files in the specified directory
-files_to_download = [f for f in files_list if f.startswith(DIRECTORY)]
-
-# Create local directory if it doesn't exist
-os.makedirs(DIRECTORY, exist_ok=True)
-
-# Download each file
-for file in files_to_download:
-    file_path = hf_hub_download(repo_id=REPO_ID, filename=file, repo_type="dataset")
-    # Copy the file to the local directory using shutil.copy2
-    shutil.copy2(file_path, os.path.join(DIRECTORY, os.path.basename(file_path)))
-
-print("Files downloaded successfully.")
-
-```
-
-**Directory Structure**
+**Directory Structure of the data**
 ```
 main/
 ├── 2Dbubble/