





from math import factorial






def       _A  (      lowerCamelCase							, lowerCamelCase   ):

   # If either of the conditions are true, the function is being asked
   # to calculate a factorial of a negative number, which is not possible
   if n < k or k < 0:
      raise ValueError("Please enter positive integers for n and k where n >= k"   )
   return factorial(lowerCamelCase   ) // (factorial(lowerCamelCase   ) * factorial(n - k   ))


if __name__ == "__main__":
  print(
      """The number of five-card hands possible from a standard""",
      f'fifty-two card deck is: {combinations(5_2, 5)}\n',
  )

  print(
      """If a class of 40 students must be arranged into groups of""",
      f'4 for group projects, there are {combinations(4_0, 4)} ways',
      """to arrange them.\n""",
  )

  print(
      """If 10 teams are competing in a Formula One race, there""",
      f'are {combinations(1_0, 3)} ways that first, second and',
      """third place can be awarded.""",
  )








import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


SCREAMING_SNAKE_CASE__       :			Dict			      =						"""
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
"""







class   __lowerCAmelCase			(					unittest.TestCase		,_UpperCamelCase  ):





   def 	_snake_case ( self      )				->  str:
      """simple docstring"""





      a__	:						Optional[int]      		=  load_tool("text-question-answering"      )
      self.tool.setup()
      a__	:						Dict      		=  load_tool("text-question-answering"					,			remote=snake_case      )





   def 	_snake_case ( self      )				->  Dict:
      """simple docstring"""





      a__	:						Optional[Any]      		=  self.tool(snake_case					,			"What did Hugging Face do in April 2021?"      )
      self.assertEqual(snake_case					,			"launched the BigScience Research Workshop"      )





   def 	_snake_case ( self      )				->  Tuple:
      """simple docstring"""





      a__	:						List[Any]      		=  self.remote_tool(snake_case					,			"What did Hugging Face do in April 2021?"      )
      self.assertEqual(snake_case					,			"launched the BigScience Research Workshop"      )





   def 	_snake_case ( self      )				->  Any:
      """simple docstring"""





      a__	:						Any      		=  self.tool(text=snake_case					,			question="What did Hugging Face do in April 2021?"      )
      self.assertEqual(snake_case					,			"launched the BigScience Research Workshop"      )





   def 	_snake_case ( self      )				->  int:
      """simple docstring"""





      a__	:						List[str]      		=  self.remote_tool(text=snake_case					,			question="What did Hugging Face do in April 2021?"      )
      self.assertEqual(snake_case					,			"launched the BigScience Research Workshop"      )

