cCiN SrSSKJr SSKJrJrJr SSKJr \R"\ 5r Sr "SS \5r "S S \5r"S S \5r/SQrg)zTensorflow mT5 model.)logging)TFT5EncoderModelTFT5ForConditionalGeneration TFT5Model) MT5ConfigT5Configc \rSrSrSrSr\rSrg) TFMT5Modela 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 ```mt5N __name__ __module__ __qualname____firstlineno____doc__ model_typer config_class__static_attributes__ra/home/james-whalen/.local/lib/python3.13/site-packages/transformers/models/mt5/modeling_tf_mt5.pyr r s (JLrr c \rSrSrSrSr\rSrg)TFMT5ForConditionalGeneration4a 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 ```rrNrrrrrr4s &JLrrc \rSrSrSrSr\rSrg)TFMT5EncoderModelLa> 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 ```rrNrrrrrrLs "JLrr)rrr N)rutilsrt5.modeling_tf_t5rrrconfiguration_mt5r get_loggerrlogger_CONFIG_FOR_DOCr rr__all__rrrr(s[YY(   H %2$@0(, Or