# coding=utf-8 # Copyright 2020 Mesh TensorFlow authors, T5 Authors and HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tensorflow mT5 model.""" from ...utils import logging from ..t5.modeling_tf_t5 import TFT5EncoderModel, TFT5ForConditionalGeneration, TFT5Model from .configuration_mt5 import MT5Config logger = logging.get_logger(__name__) _CONFIG_FOR_DOC = "T5Config" class TFMT5Model(TFT5Model): r""" This class overrides [`TFT5Model`]. Please check the superclass for the appropriate documentation alongside usage examples. Examples: ```python >>> from transformers import TFMT5Model, AutoTokenizer >>> model = TFMT5Model.from_pretrained("google/mt5-small") >>> tokenizer = AutoTokenizer.from_pretrained("google/mt5-small") >>> article = "UN Offizier sagt, dass weiter verhandelt werden muss in Syrien." >>> summary = "Weiter Verhandlung in Syrien." >>> inputs = tokenizer(article, return_tensors="tf") >>> labels = tokenizer(text_target=summary, return_tensors="tf") >>> outputs = model(input_ids=inputs["input_ids"], decoder_input_ids=labels["input_ids"]) >>> hidden_states = outputs.last_hidden_state ```""" model_type = "mt5" config_class = MT5Config class TFMT5ForConditionalGeneration(TFT5ForConditionalGeneration): r""" This class overrides [`TFT5ForConditionalGeneration`]. Please check the superclass for the appropriate documentation alongside usage examples. Examples: ```python >>> from transformers import TFMT5ForConditionalGeneration, AutoTokenizer >>> model = TFMT5ForConditionalGeneration.from_pretrained("google/mt5-small") >>> tokenizer = AutoTokenizer.from_pretrained("google/mt5-small") >>> article = "UN Offizier sagt, dass weiter verhandelt werden muss in Syrien." >>> summary = "Weiter Verhandlung in Syrien." >>> inputs = tokenizer(article, text_target=summary, return_tensors="tf") >>> outputs = model(**inputs) >>> loss = outputs.loss ```""" model_type = "mt5" config_class = MT5Config class TFMT5EncoderModel(TFT5EncoderModel): r""" This class overrides [`TFT5EncoderModel`]. Please check the superclass for the appropriate documentation alongside usage examples. Examples: ```python >>> from transformers import TFMT5EncoderModel, AutoTokenizer >>> model = TFMT5EncoderModel.from_pretrained("google/mt5-small") >>> tokenizer = AutoTokenizer.from_pretrained("google/mt5-small") >>> article = "UN Offizier sagt, dass weiter verhandelt werden muss in Syrien." >>> input_ids = tokenizer(article, return_tensors="tf").input_ids >>> outputs = model(input_ids) >>> hidden_state = outputs.last_hidden_state ```""" model_type = "mt5" config_class = MT5Config __all__ = ["TFMT5EncoderModel", "TFMT5ForConditionalGeneration", "TFMT5Model"]