code: def comparison_download(
      url,
      text_column1,
      text_column2,
      target_column,
      filename,
      save=True,
      task_type="Similarity",
      data_directory="Data",
  ):
      save_path = os.path.join(data_directory, task_type, filename)
  
      response = requests.get(url)
      _file = StringIO(response.text.replace("\r", "\n"))
      df = pd.read_csv(_file, sep=",")
      df = df.dropna(subset=[text_column1, text_column2, target_column])
  
      new_df = pd.DataFrame(columns=["Text1", "Text2", "Target"])
      new_df["Text1"], new_df["Text2"], new_df["Target"] = (
          df[text_column1],
          df[text_column2],
          df[target_column],
      )
  
      if save:
          new_df.to_csv(save_path, index=False)
  
      return new_df
  
file_path: finetune/finetune/datasets/__init__.py
imports: import hashlib
  from io import StringIO
  import os.path
  from pathlib import Path
  import requests
  import pandas
label_desc: Use image node_id 3 for calling a global function with example usage: comparison_download(url, text_column1, text_column2, target_column, filename, save, task_type, data_directory) and returns: new_df