"""
    #################################################################################################################################################################################################
    # 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 typing import TYPE_CHECKING
from ...utils import (OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available)
_import_structure = {'configuration_distilbert': ['DistilBertConfig', 'DistilBertOnnxConfig'], 'tokenization_distilbert': ['DistilBertTokenizer']}
try:
    if not is_tokenizers_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["tokenization_distilbert_fast"] = ["DistilBertTokenizerFast"]
try:
    if not is_torch_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else:
    _import_structure["modeling_distilbert"] = ["DistilBertForMaskedLM", "DistilBertForMultipleChoice", "DistilBertForQuestionAnswering", "DistilBertForSequenceClassification",
    "DistilBertForTokenClassification", "DistilBertModel", "DistilBertPreTrainedModel"]
try:
    if not is_tf_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else:
    _import_structure["modeling_tf_distilbert"] = ["TFDistilBertForMaskedLM", "TFDistilBertForMultipleChoice", "TFDistilBertForQuestionAnswering", "TFDistilBertForSequenceClassification",
    "TFDistilBertForTokenClassification", "TFDistilBertMainLayer", "TFDistilBertModel", "TFDistilBertPreTrainedModel"]
try:
    if not is_flax_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else:
    _import_structure["modeling_flax_distilbert"] = ["FlaxDistilBertForMaskedLM", "FlaxDistilBertForMultipleChoice", "FlaxDistilBertForQuestionAnswering", "FlaxDistilBertForSequenceClassification",
    "FlaxDistilBertForTokenClassification", "FlaxDistilBertModel", "FlaxDistilBertPreTrainedModel"]
if TYPE_CHECKING:
    from .configuration_distilbert import (DistilBertConfig, DistilBertOnnxConfig)
    from .tokenization_distilbert import DistilBertTokenizer
    try:
        if not is_tokenizers_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .tokenization_distilbert_fast import DistilBertTokenizerFast
    try:
        if not is_torch_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else:
        from .modeling_distilbert import (DistilBertForMaskedLM, DistilBertForMultipleChoice, DistilBertForQuestionAnswering, DistilBertForSequenceClassification,
        DistilBertForTokenClassification, DistilBertModel, DistilBertPreTrainedModel)
    try:
        if not is_tf_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else:
        from .modeling_tf_distilbert import (TFDistilBertForMaskedLM, TFDistilBertForMultipleChoice, TFDistilBertForQuestionAnswering, TFDistilBertForSequenceClassification,
        TFDistilBertForTokenClassification, TFDistilBertMainLayer, TFDistilBertModel, TFDistilBertPreTrainedModel)
    try:
        if not is_flax_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else:
        from .modeling_flax_distilbert import (FlaxDistilBertForMaskedLM, FlaxDistilBertForMultipleChoice, FlaxDistilBertForQuestionAnswering, FlaxDistilBertForSequenceClassification,
        FlaxDistilBertForTokenClassification, FlaxDistilBertModel, FlaxDistilBertPreTrainedModel)
else:
    import sys
    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
"""
    #################################################################################################################################################################################################
    # 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.                                                                 #
    #################################################################################################################################################################################################
"""
