Update README.md

README.md

@@ -43,7 +43,6 @@ Source Data
 The dataset comprises 15,836 vulnerabilities and **18,435 associated patches**. For training, we consider only those patches corresponding to vulnerabilities annotated with at least one CWE.
 
 
-
 The vulnerabilities are sourced from:
 
     - NVD CVE List — enriched with commit references
@@ -54,6 +53,30 @@ The vulnerabilities are sourced from:
 
     - CSAF feeds from vendors including Red Hat, Cisco, and CISA
 
+### How to use with datasets
+
+```python
+>>> import json
+>>> from datasets import load_dataset
+
+>>> dataset = load_dataset("CIRCL/vulnerability-cwe-patch")
+
+>>> vulnerabilities = ["CVE-2025-60249", "CVE-2025-32413"]
+
+>>> filtered_entries = dataset.filter(lambda elem: elem["id"] in vulnerabilities)
+
+>>> for entry in filtered_entries["train"]:
+...     print(entry["cwe"])
+...     for patch in entry["patches"]:
+...         print(f"  {patch['commit_message']})
+...
+CWE-79 Improper Neutralization of Input During Web Page Generation (XSS or 'Cross-site Scripting')     
+  [PATCH] fix: [security] Fixed a stored XSS vulnerability in user bios. Thanks to Dawid Czarnecki for reporting the issue.
+CWE-79 Improper Neutralization of Input During Web Page Generation (XSS or 'Cross-site Scripting')
+  [PATCH] fix: [security] sanitize user input in comments, bundles, and sightings - Escaped untrusted data in templates and tables to prevent XSS - Replaced unsafe innerHTML assignments with createElement/textContent - Encoded dynamic URLs using encodeURIComponent - Improved validation in Comment, Bundle, and Sighting models Credit: @Wachizungu
+```
+
+
 ### Schema
 
 Each example contains: