"""
    #################################################################################################################################################################################################
    # This code library is an adaptation of the original Transformers and was designed, developed and programmed by Sapiens Technology®.                                                            #
    # Any alteration and/or disclosure of this code without prior authorization is strictly prohibited and is subject to legal action that will be forwarded by the Sapiens Technology® legal team. #
    # This set of algorithms aims to download, train, fine-tune and/or infer large language models from various sources and slopes.                                                                 #
    #################################################################################################################################################################################################
"""
from ..utils import DummyObject, requires_backends
class AlbertTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class BarthezTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class BartphoTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class BertGenerationTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class BigBirdTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class CamembertTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class CodeLlamaTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class CpmTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class DebertaV2Tokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class EntityTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class ErnieMTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class XLMProphetNetTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class FNetTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class GemmaTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class GPTSw3Tokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class LayoutXLMTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class LlamaTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class M2M100Tokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class MarianTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class MBartTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class MBart50Tokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class MLukeTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class MT5Tokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class NllbTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class PegasusTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class PLBartTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class ReformerTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class RemBertTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class SapamaTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class SeamlessM4TTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class SiglipTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class Speech2TextTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class SpeechT5Tokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class T5Tokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class UdopTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class XGLMTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class XLMRobertaTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
class XLNetTokenizer(metaclass=DummyObject):
    _backends = ["sentencepiece"]
    def __init__(self, *args, **kwargs): requires_backends(self, ["sentencepiece"])
"""
    #################################################################################################################################################################################################
    # This code library is an adaptation of the original Transformers and was designed, developed and programmed by Sapiens Technology®.                                                            #
    # Any alteration and/or disclosure of this code without prior authorization is strictly prohibited and is subject to legal action that will be forwarded by the Sapiens Technology® legal team. #
    # This set of algorithms aims to download, train, fine-tune and/or infer large language models from various sources and slopes.                                                                 #
    #################################################################################################################################################################################################
"""
