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)
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from keras_nlp .models .albert .albert_preprocessor import AlbertPreprocessor
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from keras_nlp .models .albert .albert_tokenizer import AlbertTokenizer
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+ from keras_nlp .models .backbone import Backbone
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from keras_nlp .models .bart .bart_backbone import BartBackbone
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from keras_nlp .models .bart .bart_preprocessor import BartPreprocessor
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from keras_nlp .models .bart .bart_seq_2_seq_lm import BartSeq2SeqLM
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from keras_nlp .models .roberta .roberta_tokenizer import RobertaTokenizer
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from keras_nlp .models .t5 .t5_backbone import T5Backbone
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from keras_nlp .models .t5 .t5_tokenizer import T5Tokenizer
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+ from keras_nlp .models .task import Task
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from keras_nlp .models .whisper .whisper_audio_feature_extractor import (
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WhisperAudioFeatureExtractor ,
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)
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# See the License for the specific language governing permissions and
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# limitations under the License.
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+ from keras_nlp .api_export import keras_nlp_export
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from keras_nlp .backend import config
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from keras_nlp .backend import keras
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from keras_nlp .utils .preset_utils import check_preset_class
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from keras_nlp .utils .python_utils import format_docstring
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- @keras . saving . register_keras_serializable ( package = "keras_nlp" )
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+ @keras_nlp_export ( "keras_nlp.models.Backbone " )
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class Backbone (keras .Model ):
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def __init__ (self , * args , dtype = None , ** kwargs ):
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super ().__init__ (* args , ** kwargs )
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from rich import markup
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from rich import table as rich_table
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+ from keras_nlp .api_export import keras_nlp_export
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from keras_nlp .backend import config
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from keras_nlp .backend import keras
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from keras_nlp .utils .keras_utils import print_msg
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from keras_nlp .utils .python_utils import format_docstring
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- @keras . saving . register_keras_serializable ( package = "keras_nlp" )
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+ @keras_nlp_export ( "keras_nlp.models.Task " )
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class Task (PipelineModel ):
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"""Base class for Task models."""
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