<jupyter_start><jupyter_text><jupyter_code><jupyter_output><empty_output><jupyter_text>**1.SETUP**Since we are dealing with large no of data to make speed faster change setting of notebook at runtime.We can do this by two ways --1)Edit ----> Notebook Settings --- Select Hardware Accelerator -- GPU2)Runtime --->Change Runtime type ---Select Hardware Accelerator -- GPU<jupyter_code>import tensorflow as tf

# Get the GPU device name.
device_name = tf.test.gpu_device_name()

# The device name should look like the following:
if device_name == '/device:GPU:0':
    print('Found GPU at: {}'.format(device_name))
else:
    raise SystemError('GPU device not found')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11416184971098266, 'fraction_numerical': 0.005780346820809248, 'mean_word_length': 5.078947368421052, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 11, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '585014', 'license': 'Apache-2.0', 'n_tokens_mistral': 214, 'n_tokens_neox': 212, 'n_words': 70, 'path': '00BERT_SETUP.ipynb', 'repo_name': 'Swty13/NLP-Books', 'size': '692'}