
    sg                         d Z ddlmZ ddlmZmZmZ ddlmZ  ej                  e
      ZdZ G d d	e      Z G d
 de      Z G d de      Zy)zTensorflow mT5 model.   )logging   )TFT5EncoderModelTFT5ForConditionalGeneration	TFT5Model   )	MT5ConfigT5Configc                       e Zd ZdZdZeZy)
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____doc__
model_typer	   config_class     Z/var/www/html/venv/lib/python3.12/site-packages/transformers/models/mt5/modeling_tf_mt5.pyr   r      s    ( JLr   r   c                       e Zd ZdZdZeZy)TFMT5ForConditionalGenerationa  
    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
    ```r   Nr   r   r   r   r   r   4   s    & JLr   r   c                       e Zd ZdZdZeZy)TFMT5EncoderModelan  
    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
    ```r   Nr   r   r   r   r   r   L   s    " JLr   r   N)r   utilsr   t5.modeling_tf_t5r   r   r   configuration_mt5r	   
get_loggerr   logger_CONFIG_FOR_DOCr   r   r   r   r   r   <module>r"      sU      Y Y ( 
		H	% 2$@ 0( r   