<jupyter_start><jupyter_text>Paraphrases Template<jupyter_code>from google.colab import drive
drive.mount('/content/drive')
import pandas as pd
dt = pd.read_csv('/content/drive/My Drive/data/ihlt/test-gold/STS.input.SMTeuroparl.txt',sep='\t',header=None)
dt.head()
dt['gs'] = pd.read_csv('/content/drive/My Drive/data/ihlt/test-gold/STS.gs.SMTeuroparl.txt',sep='\t',header=None)
dt.shape
dt.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.18032786885245902, 'fraction_numerical': 0.0, 'mean_word_length': 6.925925925925926, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '43005', 'license': 'MIT', 'n_tokens_mistral': 176, 'n_tokens_neox': 171, 'n_words': 19, 'path': 's2/codes/readPars.ipynb', 'repo_name': 'gebakx/ihlt', 'size': '427'}