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https://github.com/huggingface/transformers.git
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8b240a0661
* Add cross attentions to TFGPT2Model * Add TFEncoderDecoderModel * Add TFBaseModelOutputWithPoolingAndCrossAttentions * Add cross attentions to TFBertModel * Fix past or past_key_values argument issue * Fix generation * Fix save and load * Add some checks and comments * Clean the code that deals with past keys/values * Add kwargs to processing_inputs * Add serving_output to TFEncoderDecoderModel * Some cleaning + fix use_cache value issue * Fix tests + add bert2bert/bert2gpt2 tests * Fix more tests * Ignore crossattention.bias when loading GPT2 weights into TFGPT2 * Fix return_dict_in_generate in tf generation * Fix is_token_logit_eos_token bug in tf generation * Finalize the tests after fixing some bugs * Fix another is_token_logit_eos_token bug in tf generation * Add/Update docs * Add TFBertEncoderDecoderModelTest * Clean test script * Add TFEncoderDecoderModel to the library * Add cross attentions to TFRobertaModel * Add TFRobertaEncoderDecoderModelTest * make style * Change the way of position_ids computation * bug fix * Fix copies in tf_albert * Remove some copied from and apply some fix-copies * Remove some copied * Add cross attentions to some other TF models * Remove encoder_hidden_states from TFLayoutLMModel.call for now * Make style * Fix TFRemBertForCausalLM * Revert the change to longformer + Remove copies * Revert the change to albert and convbert + Remove copies * make quality * make style * Add TFRembertEncoderDecoderModelTest * make quality and fix-copies * test TFRobertaForCausalLM * Fixes for failed tests * Fixes for failed tests * fix more tests * Fixes for failed tests * Fix Auto mapping order * Fix TFRemBertEncoder return value * fix tf_rembert * Check copies are OK * Fix missing TFBaseModelOutputWithPastAndCrossAttentions is not defined * Add TFEncoderDecoderModelSaveLoadTests * fix tf weight loading * check the change of use_cache * Revert the change * Add missing test_for_causal_lm for TFRobertaModelTest * Try cleaning past * fix _reorder_cache * Revert some files to original versions * Keep as many copies as possible * Apply suggested changes - Use raise ValueError instead of assert * Move import to top * Fix wrong require_torch * Replace more assert by raise ValueError * Add test_pt_tf_model_equivalence (the test won't pass for now) * add test for loading/saving * finish * finish * Remove test_pt_tf_model_equivalence * Update tf modeling template * Remove pooling, added in the prev. commit, from MainLayer * Update tf modeling test template * Move inputs["use_cache"] = False to modeling_tf_utils.py * Fix torch.Tensor in the comment * fix use_cache * Fix missing use_cache in ElectraConfig * Add a note to from_pretrained * Fix style * Change test_encoder_decoder_save_load_from_encoder_decoder_from_pt * Fix TFMLP (in TFGPT2) activation issue * Fix None past_key_values value in serving_output * Don't call get_encoderdecoder_model in TFEncoderDecoderModelTest.test_configuration_tie until we have a TF checkpoint on Hub * Apply review suggestions - style for cross_attns in serving_output * Apply review suggestions - change assert + docstrings * break the error message to respect the char limit * deprecate the argument past * fix docstring style * Update the encoder-decoder rst file * fix Unknown interpreted text role "method" * fix typo Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
413 lines
15 KiB
ReStructuredText
413 lines
15 KiB
ReStructuredText
..
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Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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Model outputs
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-----------------------------------------------------------------------------------------------------------------------
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All models have outputs that are instances of subclasses of :class:`~transformers.file_utils.ModelOutput`. Those are
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data structures containing all the information returned by the model, but that can also be used as tuples or
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dictionaries.
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Let's see of this looks on an example:
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.. code-block::
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from transformers import BertTokenizer, BertForSequenceClassification
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import torch
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tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
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model = BertForSequenceClassification.from_pretrained('bert-base-uncased')
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inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
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labels = torch.tensor([1]).unsqueeze(0) # Batch size 1
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outputs = model(**inputs, labels=labels)
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The ``outputs`` object is a :class:`~transformers.modeling_outputs.SequenceClassifierOutput`, as we can see in the
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documentation of that class below, it means it has an optional ``loss``, a ``logits`` an optional ``hidden_states`` and
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an optional ``attentions`` attribute. Here we have the ``loss`` since we passed along ``labels``, but we don't have
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``hidden_states`` and ``attentions`` because we didn't pass ``output_hidden_states=True`` or
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``output_attentions=True``.
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You can access each attribute as you would usually do, and if that attribute has not been returned by the model, you
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will get ``None``. Here for instance ``outputs.loss`` is the loss computed by the model, and ``outputs.attentions`` is
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``None``.
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When considering our ``outputs`` object as tuple, it only considers the attributes that don't have ``None`` values.
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Here for instance, it has two elements, ``loss`` then ``logits``, so
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.. code-block::
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outputs[:2]
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will return the tuple ``(outputs.loss, outputs.logits)`` for instance.
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When considering our ``outputs`` object as dictionary, it only considers the attributes that don't have ``None``
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values. Here for instance, it has two keys that are ``loss`` and ``logits``.
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We document here the generic model outputs that are used by more than one model type. Specific output types are
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documented on their corresponding model page.
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ModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.file_utils.ModelOutput
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:members: to_tuple
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BaseModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.BaseModelOutput
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:members:
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BaseModelOutputWithPooling
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.BaseModelOutputWithPooling
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:members:
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BaseModelOutputWithCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.BaseModelOutputWithCrossAttentions
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:members:
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BaseModelOutputWithPoolingAndCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.BaseModelOutputWithPoolingAndCrossAttentions
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:members:
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BaseModelOutputWithPast
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.BaseModelOutputWithPast
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:members:
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BaseModelOutputWithPastAndCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.BaseModelOutputWithPastAndCrossAttentions
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:members:
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Seq2SeqModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.Seq2SeqModelOutput
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:members:
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CausalLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.CausalLMOutput
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:members:
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CausalLMOutputWithCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.CausalLMOutputWithCrossAttentions
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:members:
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CausalLMOutputWithPast
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.CausalLMOutputWithPast
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:members:
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MaskedLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.MaskedLMOutput
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:members:
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Seq2SeqLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.Seq2SeqLMOutput
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:members:
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NextSentencePredictorOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.NextSentencePredictorOutput
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:members:
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SequenceClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.SequenceClassifierOutput
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:members:
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Seq2SeqSequenceClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.Seq2SeqSequenceClassifierOutput
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:members:
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MultipleChoiceModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.MultipleChoiceModelOutput
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:members:
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TokenClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.TokenClassifierOutput
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:members:
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QuestionAnsweringModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.QuestionAnsweringModelOutput
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:members:
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Seq2SeqQuestionAnsweringModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_outputs.Seq2SeqQuestionAnsweringModelOutput
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:members:
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TFBaseModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFBaseModelOutput
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:members:
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TFBaseModelOutputWithPooling
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFBaseModelOutputWithPooling
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:members:
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TFBaseModelOutputWithPoolingAndCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFBaseModelOutputWithPoolingAndCrossAttentions
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:members:
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TFBaseModelOutputWithPast
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFBaseModelOutputWithPast
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:members:
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TFBaseModelOutputWithPastAndCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFBaseModelOutputWithPastAndCrossAttentions
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:members:
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TFSeq2SeqModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFSeq2SeqModelOutput
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:members:
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TFCausalLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFCausalLMOutput
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:members:
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TFCausalLMOutputWithCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFCausalLMOutputWithCrossAttentions
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:members:
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TFCausalLMOutputWithPast
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFCausalLMOutputWithPast
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:members:
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TFMaskedLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFMaskedLMOutput
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:members:
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TFSeq2SeqLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFSeq2SeqLMOutput
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:members:
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TFNextSentencePredictorOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFNextSentencePredictorOutput
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:members:
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TFSequenceClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFSequenceClassifierOutput
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:members:
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TFSeq2SeqSequenceClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFSeq2SeqSequenceClassifierOutput
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:members:
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TFMultipleChoiceModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFMultipleChoiceModelOutput
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:members:
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TFTokenClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFTokenClassifierOutput
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:members:
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TFQuestionAnsweringModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFQuestionAnsweringModelOutput
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:members:
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TFSeq2SeqQuestionAnsweringModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_tf_outputs.TFSeq2SeqQuestionAnsweringModelOutput
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:members:
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FlaxBaseModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxBaseModelOutput
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FlaxBaseModelOutputWithPast
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxBaseModelOutputWithPast
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FlaxBaseModelOutputWithPooling
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxBaseModelOutputWithPooling
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FlaxBaseModelOutputWithPastAndCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxBaseModelOutputWithPastAndCrossAttentions
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FlaxSeq2SeqModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxSeq2SeqModelOutput
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FlaxCausalLMOutputWithCrossAttentions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxCausalLMOutputWithCrossAttentions
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FlaxMaskedLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxMaskedLMOutput
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FlaxSeq2SeqLMOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxSeq2SeqLMOutput
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FlaxNextSentencePredictorOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxNextSentencePredictorOutput
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FlaxSequenceClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxSequenceClassifierOutput
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FlaxSeq2SeqSequenceClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxSeq2SeqSequenceClassifierOutput
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FlaxMultipleChoiceModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxMultipleChoiceModelOutput
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FlaxTokenClassifierOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxTokenClassifierOutput
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FlaxQuestionAnsweringModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxQuestionAnsweringModelOutput
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FlaxSeq2SeqQuestionAnsweringModelOutput
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.modeling_flax_outputs.FlaxSeq2SeqQuestionAnsweringModelOutput
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