tf
        >>> from transformers import AutoTokenizer, RagRetriever, TFRagTokenForGeneration

        >>> tokenizer = AutoTokenizer.from_pretrained("facebook/rag-token-nq")
        >>> retriever = RagRetriever.from_pretrained(
        ...     "facebook/rag-token-nq", index_name="exact", use_dummy_dataset=True
        ... )
        >>> # initialize with RagRetriever to do everything in one forward call
        >>> model = TFRagTokenForGeneration.from_pretrained("facebook/rag-token-nq", retriever=retriever, from_pt=True)

        >>> input_dict = tokenizer.prepare_seq2seq_batch(
        ...     "How many people live in Paris?", "In Paris, there are 10 million people.", return_tensors="tf"
        ... )
        >>> outputs = model(input_dict, output_retrieved=True)

        >>> # or use retriever separately
        >>> # 1. Encode
        >>> input_ids = input_dict["input_ids"]
        >>> question_hidden_states = model.question_encoder(input_ids)[0]
        >>> # 2. Retrieve
        >>> docs_dict = retriever(input_ids.numpy(), question_hidden_states.numpy(), return_tensors="tf")
        >>> doc_scores = tf.squeeze(
        ...     tf.matmul(
        ...         tf.expand_dims(question_hidden_states, axis=1), docs_dict["retrieved_doc_embeds"], transpose_b=True
        ...     ),
        ...     axis=1,
        ... )
        >>> # 3. Forward to generator
        >>> outputs = model(
        ...     inputs=None,
        ...     context_input_ids=docs_dict["context_input_ids"],
        ...     context_attention_mask=docs_dict["context_attention_mask"],
        ...     doc_scores=doc_scores,
        ...     decoder_input_ids=input_dict["labels"],
        ... )

        >>> # or directly generate
        >>> generated = model.generate(
        ...     context_input_ids=docs_dict["context_input_ids"],
        ...     context_attention_mask=docs_dict["context_attention_mask"],
        ...     doc_scores=doc_scores,
        ... )
        >>> generated_string = tokenizer.batch_decode(generated, skip_special_tokens=True)
        ```r„