Upload 2 files

wikitext.py

@@ -0,0 +1,47 @@
+from bs4 import BeautifulSoup
+from datasets import load_dataset
+
+def get_titles(file_path):
+    # get the titles from html file (html file is downloaded from https://de.wikipedia.org/wiki/Wikipedia:Exzellente_Artikel)
+    with open(file_path, 'r') as f:
+        html_content = f.read()
+    soup = BeautifulSoup(html_content, 'html.parser')
+    # Find the <tbody> element (you can modify this based on your HTML structure)
+    tbody = soup.find('tbody')
+    # Extract all <tr> elements within the <tbody> element
+    trs = tbody.find_all('tr')
+    # Remove the first two <tr> elements
+    trs = trs[2:]
+    # Extract title attributes from the remaining <tr> elements
+    titles = []
+    for tr in trs:
+        if tr is None or tr.find('a') is None:
+            continue
+        a_tags = tr.find_all('a')
+        for a_tag in a_tags:
+            if a_tag and 'title' in a_tag.attrs:
+                titles.append(a_tag['title'])
+    return titles
+
+if __name__ == '__main__':
+    titles_exzellent = get_titles('exzellent.txt')
+    #titles_lesenswert = get_titles('lesenswert.txt')
+    titles = titles_exzellent #+ titles_lesenswert
+    titles = list(set(titles))
+    with open('titles.txt', 'w') as f:
+        for title in titles:
+            f.write(title + '\n')
+    
+    # Get wikipedia dataset
+    dataset = load_dataset("graelo/wikipedia", "20230901.de", split="train")
+    # Filter dataset
+    dataset = dataset.filter(lambda example: example['title'] in titles, num_proc=64)
+    dataset.map(lambda x: {'text': f"# {x['title']}\n\n{x['text']}"}, remove_columns=['title'], num_proc=64)
+    # Save dataset
+    used_title = [example['title'] for example in dataset]
+    non_used_title = [title for title in titles if title not in used_title]
+    print(f'Number of used titles: {len(used_title)}')
+    print(f'Number of non used titles: {len(non_used_title)}')
+    print(non_used_title[:20])
+
+    dataset.push_to_hub("LeoLM/wiki_de_exzellent", private=True)

wikitext_en.py

@@ -0,0 +1,36 @@
+from bs4 import BeautifulSoup
+from datasets import load_dataset
+
+def get_titles(file_path):
+    # Get titles from html file (html file is downloaded from https://en.wikipedia.org/wiki/Wikipedia:Featured_articles)
+    with open(file_path, 'r') as f:
+        html_content = f.read()
+    soup = BeautifulSoup(html_content, 'html.parser')
+    div = soup.find_all('div', attrs={'class': 'wp-fa-contents'})
+    titles = []
+    for d in div:
+        if d is None or d.find('a') is None:
+            continue
+        a_tags = d.find_all('a')
+        for a_tag in a_tags:
+            if a_tag and 'title' in a_tag.attrs:
+                titles.append(a_tag['title'])
+    return titles
+
+
+if __name__ == '__main__':
+    titles = get_titles('featured.html')
+    titles = list(set(titles))
+    
+    # Get wikipedia dataset
+    dataset = load_dataset("graelo/wikipedia", "20230901.en", split="train")
+    # Filter dataset
+    dataset = dataset.filter(lambda example: example['title'] in titles, num_proc=64)
+    dataset.map(lambda x: {'text': f"# {x['title']}\n\n{x['text']}"}, remove_columns=['title'], num_proc=64)
+    # Save dataset
+    used_title = [example['title'] for example in dataset]
+    non_used_title = [title for title in titles if title not in used_title]
+    print(f'Number of used titles: {len(used_title)}')
+    print(f'Number of non used titles: {len(non_used_title)}')
+    print(non_used_title[:20])
+    dataset.push_to_hub("LeoLM/wiki_en_featured", private=True)