"""
    #################################################################################################################################################################################################
    # 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_opt": ["OPTConfig"]}
try:
    if not is_torch_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["modeling_opt"] = ["OPTForCausalLM", "OPTModel", "OPTPreTrainedModel", "OPTForSequenceClassification", "OPTForQuestionAnswering"]
try:
    if not is_tf_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["modeling_tf_opt"] = ["TFOPTForCausalLM", "TFOPTModel", "TFOPTPreTrainedModel"]
try:
    if not is_flax_available(): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable: pass
else: _import_structure["modeling_flax_opt"] = ["FlaxOPTForCausalLM", "FlaxOPTModel", "FlaxOPTPreTrainedModel"]
if TYPE_CHECKING:
    from .configuration_opt import OPTConfig
    try:
        if not is_torch_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .modeling_opt import (OPTForCausalLM, OPTForQuestionAnswering, OPTForSequenceClassification, OPTModel, OPTPreTrainedModel)
    try:
        if not is_tf_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel
    try:
        if not is_flax_available(): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: pass
    else: from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel
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.                                                                 #
    #################################################################################################################################################################################################
"""
