





'''simple docstring'''

class        __lowerCAmelCase  :






							"""simple docstring"""





							def __init__(							self     :	Any ,				lowerCAmelCase__     :	List[str]=None  )					->  Optional[Any]:

												'''simple docstring'''




												_UpperCamelCase       					= data
												_UpperCamelCase       					= None







							def __repr__(							self     :	Optional[Any]  )					->  Optional[int]:

												'''simple docstring'''




												_UpperCamelCase       					= ''''''
												_UpperCamelCase       					= self
												while temp:
																	string_rep += f"""<{temp.data}> ---> """
																	_UpperCamelCase       					= temp.next
												string_rep += "<END>"
												return string_rep







def       a__       (       lowercase      :  List[Any]   )	->	Optional[int]:





					"""simple docstring"""

					if not elements_list:
										raise Exception('''The Elements List is empty'''   )

					# Set first element as Head
					_UpperCamelCase       					= Node(elements_list[0]   )
					_UpperCamelCase       					= head
					# Loop through elements from position 1
					for data in elements_list[1:]:
										_UpperCamelCase       					= Node(lowercase   )
										_UpperCamelCase       					= current.next
					return head


lowercase__		:    Tuple =       [1, 3, 5, 32, 44, 12, 43]
print(F"""List: {list_data}""")
print('Creating Linked List from List.')
lowercase__		:    Dict =       make_linked_list(list_data)
print('Linked List:')




print(linked_list)










'''simple docstring'''

lowercase__		:    Tuple =       '\n# Transformers installation\n! pip install transformers datasets evaluate\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

lowercase__		:    Union[str, Any] =       [{'type': 'code', 'content': INSTALL_CONTENT}]
lowercase__		:    str =       {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}



