






import unittest
from pathlib import Path
from shutil import copyfile

from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__snake_case      :      Optional[Any]             =       get_tests_dir("""fixtures/test_sentencepiece.model""")

if is_sentencepiece_available():
					import sentencepiece as sp


__snake_case      :      List[Any]             =       5
__snake_case      :      Union[str, Any]             =       10


@require_sentencepiece
@require_tokenizers
class       __SCREAMING_SNAKE_CASE   (				__lowercase						,   unittest.TestCase):
						_SCREAMING_SNAKE_CASE		:    List[str]						=   SpeechaTextTokenizer
						_SCREAMING_SNAKE_CASE		:    Any						=   False
						_SCREAMING_SNAKE_CASE		:    str						=   True






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												super().setUp()

												lowerCAmelCase__        =  sp.SentencePieceProcessor()
												spm_model.Load(_UpperCamelCase				)
												lowerCAmelCase__        =  ['<s>', '<pad>', '</s>', '<unk>']

												vocab += [spm_model.IdToPiece(id_				) for id_ in range(len(_UpperCamelCase				)				)]
												lowerCAmelCase__        =  dict(zip(_UpperCamelCase       ,  range(len(_UpperCamelCase				)				)				)				)

												lowerCAmelCase__        =  Path(self.tmpdirname				)
												save_json(_UpperCamelCase       ,  save_dir / VOCAB_FILES_NAMES['vocab_file']				)
												if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
																		copyfile(_UpperCamelCase       ,  save_dir / VOCAB_FILES_NAMES['spm_file']				)

												lowerCAmelCase__        =  SpeechaTextTokenizer.from_pretrained(self.tmpdirname				)
												tokenizer.save_pretrained(self.tmpdirname				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  '<pad>'
												lowerCAmelCase__        =  1

												self.assertEqual(self.get_tokenizer()._convert_token_to_id(_UpperCamelCase				)       ,  _UpperCamelCase				)
												self.assertEqual(self.get_tokenizer()._convert_id_to_token(_UpperCamelCase				)       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  list(self.get_tokenizer().get_vocab().keys()				)

												self.assertEqual(vocab_keys[0]       ,  '<s>'				)
												self.assertEqual(vocab_keys[1]       ,  '<pad>'				)
												self.assertEqual(vocab_keys[-1]       ,  'j'				)
												self.assertEqual(len(_UpperCamelCase				)       ,  10_01				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												self.assertEqual(self.get_tokenizer().vocab_size       ,  10_01				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  SpeechaTextTokenizer.from_pretrained(self.tmpdirname				)

												lowerCAmelCase__        =  tokenizer.tokenize('This is a test'				)
												self.assertListEqual(_UpperCamelCase       ,  ['▁This', '▁is', '▁a', '▁t', 'est']				)

												self.assertListEqual(
												    tokenizer.convert_tokens_to_ids(_UpperCamelCase				)       ,  [2_89, 50, 14, 1_74, 3_86]       ,  )

												lowerCAmelCase__        =  tokenizer.tokenize('I was born in 92000, and this is falsé.'				)
												self.assertListEqual(
												    _UpperCamelCase       ,  [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']       ,  )
												lowerCAmelCase__        =  tokenizer.convert_tokens_to_ids(_UpperCamelCase				)
												self.assertListEqual(_UpperCamelCase       ,  [12, 25, 88, 59, 28, 23, 11, 4, 6_06, 3_51, 3_51, 3_51, 7, 16, 70, 50, 76, 84, 10, 4, 8]				)

												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(_UpperCamelCase				)
												self.assertListEqual(
												    _UpperCamelCase       ,  [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']       ,  )







						@slow
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												# fmt: off
												lowerCAmelCase__        =  {'input_ids': [[37_91, 7_97, 31, 11, 64, 7_97, 31, 24_29, 4_33, 12, 11_76, 12, 20, 7_86, 9_15, 1_42, 24_13, 2_40, 37, 32_38, 7_97, 31, 11, 35, 93, 9_15, 1_42, 24_13, 2_40, 37, 55_40, 5_67, 12_76, 93, 37, 6_10, 40, 62, 4_55, 6_57, 10_42, 1_23, 7_80, 1_77, 37, 3_09, 2_41, 12_98, 5_14, 20, 2_92, 27_37, 1_14, 24_69, 2_41, 85, 64, 3_02, 5_48, 5_28, 4_23, 4, 5_09, 4_06, 4_23, 37, 6_01, 4, 7_77, 3_02, 5_48, 5_28, 4_23, 2_84, 4, 33_88, 5_11, 4_59, 4, 35_55, 40, 3_21, 3_02, 7_05, 4, 33_88, 5_11, 5_83, 3_26, 5, 5, 5, 62, 33_10, 5_60, 1_77, 26_80, 2_17, 15_08, 32, 31, 8_53, 4_18, 64, 5_83, 5_11, 16_05, 62, 35, 93, 5_60, 1_77, 26_80, 2_17, 15_08, 15_21, 64, 5_83, 5_11, 5_19, 62, 20, 15_15, 7_64, 20, 1_49, 2_61, 56_25, 79_72, 20, 55_40, 5_67, 12_76, 93, 39_25, 16_75, 11, 15, 8_02, 79_72, 5_76, 2_17, 15_08, 11, 35, 93, 12_53, 24_41, 15, 2_89, 6_52, 31, 4_16, 3_21, 38_42, 1_15, 40, 9_11, 8, 4_76, 6_19, 4, 3_80, 1_42, 4_23, 3_35, 2_40, 35, 93, 2_64, 8, 11, 3_35, 5_69, 4_20, 1_63, 5, 2], [2_60, 5_48, 5_28, 4_23, 20, 4_51, 20, 26_81, 11_53, 34_34, 20, 55_40, 37, 5_67, 1_26, 12_53, 24_41, 33_76, 4_49, 2_10, 4_31, 15_63, 1_77, 7_67, 55_40, 11, 12_03, 4_72, 11, 29_53, 6_85, 2_85, 3_64, 7_06, 11_53, 20, 67_99, 20, 28_69, 20, 44_64, 1_26, 40, 24_29, 20, 10_40, 8_66, 26_64, 4_18, 20, 3_18, 20, 17_26, 1_86, 20, 2_65, 5_22, 35, 93, 21_91, 46_34, 20, 10_40, 12, 67_99, 15, 2_28, 23_56, 1_42, 31, 11, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [25_75, 26_66, 6_84, 15_82, 11_76, 12, 6_27, 1_49, 6_19, 20, 49_02, 5_63, 11, 20, 1_49, 2_61, 34_20, 23_56, 1_74, 1_42, 47_14, 1_31, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
												# fmt: on

												self.tokenizer_integration_test_util(
												    expected_encoding=_UpperCamelCase       ,  model_name='facebook/s2t-small-mustc-en-de-st'       ,  revision='a14f04cf0776c02f62a8cb800cf7909e15ea23ad'       ,  )




@require_sentencepiece
class       __SCREAMING_SNAKE_CASE   (				unittest.TestCase):
						_SCREAMING_SNAKE_CASE		:    Union[str, Any]						=   '''valhalla/s2t_mustc_multilinguial_medium'''

						_SCREAMING_SNAKE_CASE		:    Union[str, Any]						=   '''C\'est trop cool'''
						_SCREAMING_SNAKE_CASE		:    Optional[int]						=   '''Esto es genial'''






						@classmethod
						def  UpperCamelCase__ (		cls				):






												"""simple docstring"""
												lowerCAmelCase__        =  SpeechaTextTokenizer.from_pretrained(cls.checkpoint_name				)
												return cls






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												self.assertEqual(self.tokenizer.lang_code_to_id['pt']       ,  4				)
												self.assertEqual(self.tokenizer.lang_code_to_id['ru']       ,  6				)
												self.assertEqual(self.tokenizer.lang_code_to_id['it']       ,  9				)
												self.assertEqual(self.tokenizer.lang_code_to_id['de']       ,  11				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												self.assertEqual(self.tokenizer.vocab_size       ,  1_00_00				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												self.assertIn(_UpperCamelCase       ,  self.tokenizer.all_special_ids				)
												lowerCAmelCase__        =  [ES_CODE, 4, 16_01, 47, 76_47, 2]
												lowerCAmelCase__        =  self.tokenizer.decode(_UpperCamelCase       ,  skip_special_tokens=_UpperCamelCase				)
												lowerCAmelCase__        =  self.tokenizer.decode(generated_ids[1:]       ,  skip_special_tokens=_UpperCamelCase				)
												self.assertEqual(_UpperCamelCase       ,  _UpperCamelCase				)
												self.assertNotIn(self.tokenizer.eos_token       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  'fr'
												lowerCAmelCase__        =  self.tokenizer(self.french_text				).input_ids
												self.assertEqual(encoded[0]       ,  _UpperCamelCase				)
												self.assertEqual(encoded[-1]       ,  self.tokenizer.eos_token_id				)







						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  'fr'
												self.assertListEqual(self.tokenizer.prefix_tokens       ,  [FR_CODE]				)

												lowerCAmelCase__        =  'es'
												self.assertListEqual(self.tokenizer.prefix_tokens       ,  [ES_CODE]				)













import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class       __SCREAMING_SNAKE_CASE   (				__lowercase						,   unittest.TestCase):
						_SCREAMING_SNAKE_CASE		:    Tuple						=   BarthezTokenizer
						_SCREAMING_SNAKE_CASE		:    int						=   BarthezTokenizerFast
						_SCREAMING_SNAKE_CASE		:    Dict						=   True
						_SCREAMING_SNAKE_CASE		:    Tuple						=   True






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												super().setUp()

												lowerCAmelCase__        =  BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez'				)
												tokenizer.save_pretrained(self.tmpdirname				)
												tokenizer.save_pretrained(self.tmpdirname       ,  legacy_format=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  '<pad>'
												lowerCAmelCase__        =  1

												self.assertEqual(self.get_tokenizer()._convert_token_to_id(_UpperCamelCase				)       ,  _UpperCamelCase				)
												self.assertEqual(self.get_tokenizer()._convert_id_to_token(_UpperCamelCase				)       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  list(self.get_tokenizer().get_vocab().keys()				)

												self.assertEqual(vocab_keys[0]       ,  '<s>'				)
												self.assertEqual(vocab_keys[1]       ,  '<pad>'				)
												self.assertEqual(vocab_keys[-1]       ,  '<mask>'				)
												self.assertEqual(len(_UpperCamelCase				)       ,  10_11_22				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												self.assertEqual(self.get_tokenizer().vocab_size       ,  10_11_22				)






						@require_torch
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  ['A long paragraph for summarization.', 'Another paragraph for summarization.']
												lowerCAmelCase__        =  [0, 57, 30_18, 7_03_07, 91, 2]

												lowerCAmelCase__        =  self.tokenizer(
												    _UpperCamelCase       ,  max_length=len(_UpperCamelCase				)       ,  padding=_UpperCamelCase       ,  truncation=_UpperCamelCase       ,  return_tensors='pt'				)
												self.assertIsInstance(_UpperCamelCase       ,  _UpperCamelCase				)

												self.assertEqual((2, 6)       ,  batch.input_ids.shape				)
												self.assertEqual((2, 6)       ,  batch.attention_mask.shape				)
												lowerCAmelCase__        =  batch.input_ids.tolist()[0]
												self.assertListEqual(_UpperCamelCase       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												if not self.test_rust_tokenizer:
																		return

												lowerCAmelCase__        =  self.get_tokenizer()
												lowerCAmelCase__        =  self.get_rust_tokenizer()

												lowerCAmelCase__        =  'I was born in 92000, and this is falsé.'

												lowerCAmelCase__        =  tokenizer.tokenize(_UpperCamelCase				)
												lowerCAmelCase__        =  rust_tokenizer.tokenize(_UpperCamelCase				)
												self.assertListEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
												lowerCAmelCase__        =  rust_tokenizer.encode(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
												self.assertListEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												lowerCAmelCase__        =  self.get_rust_tokenizer()
												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase				)
												lowerCAmelCase__        =  rust_tokenizer.encode(_UpperCamelCase				)
												self.assertListEqual(_UpperCamelCase       ,  _UpperCamelCase				)







						@slow
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												# fmt: off
												lowerCAmelCase__        =  {'input_ids': [[0, 4_90, 1_43_28, 45_07, 3_54, 47, 4_36_69, 95, 25, 7_81_17, 2_02_15, 1_97_79, 1_90, 22, 4_00, 4, 3_53_43, 8_03_10, 6_03, 86, 2_49_37, 1_05, 3_34_38, 9_47_62, 1_96, 3_96_42, 7, 15, 1_59_33, 1_73, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 1_05_34, 87, 25, 66, 33_58, 1_96, 5_52_89, 8, 8_29_61, 81, 22_04, 7_52_03, 7, 15, 7_63, 1_29_56, 2_16, 1_78, 1_43_28, 95_95, 13_77, 6_96_93, 7, 4_48, 7_10_21, 1_96, 1_81_06, 14_37, 1_39_74, 1_08, 90_83, 4, 4_93_15, 7, 39, 86, 13_26, 27_93, 4_63_33, 4, 4_48, 1_96, 7_45_88, 7, 4_93_15, 7, 39, 21, 8_22, 3_84_70, 74, 21, 6_67_23, 6_24_80, 8, 2_20_50, 5, 2]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
												# fmt: on

												# moussaKam/mbarthez is a french model. So we also use french texts.
												lowerCAmelCase__        =  [
												    'Le transformeur est un modèle d\'apprentissage profond introduit en 2017, '
												    'utilisé principalement dans le domaine du traitement automatique des langues (TAL).',
												    'À l\'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus '
												    'pour gérer des données séquentielles, telles que le langage naturel, pour des tâches '
												    'telles que la traduction et la synthèse de texte.',
												]

												self.tokenizer_integration_test_util(
												    expected_encoding=_UpperCamelCase       ,  model_name='moussaKam/mbarthez'       ,  revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'       ,  sequences=_UpperCamelCase       ,  )





