<jupyter_start><jupyter_text>Find models and source code here https://github.com/google-research/bert<jupyter_code># 1. Base uncased
url = 'https://storage.googleapis.com/bert_models/2018_10_18/uncased_L-12_H-768_A-12.zip'
name = 'uncased_L-12_H-768_A-12'
download_and_convert(url, name)

# 2. Large uncased
url = 'https://storage.googleapis.com/bert_models/2018_10_18/uncased_L-24_H-1024_A-16.zip'
name = 'uncased_L-24_H-1024_A-16'
download_and_convert(url, name)

# 3. Base cased
url = 'https://storage.googleapis.com/bert_models/2018_10_18/cased_L-12_H-768_A-12.zip'
name = 'cased_L-12_H-768_A-12'
download_and_convert(url, name)

# 4. Large cased
url = 'https://storage.googleapis.com/bert_models/2018_10_18/cased_L-24_H-1024_A-16.zip'
name = 'cased_L-24_H-1024_A-16'
download_and_convert(url, name)

print('upload all generated models from folder "models"')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14237668161434977, 'fraction_numerical': 0.10762331838565023, 'mean_word_length': 5.816793893129771, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 5, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '380425', 'license': 'Apache-2.0', 'n_tokens_mistral': 438, 'n_tokens_neox': 372, 'n_words': 50, 'path': 'python/tensorflow/bert/create_bert.ipynb', 'repo_name': 'picachu93/spark-nlp', 'size': '892'}