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Source code for transformers.models.mbart.modeling_mbart
# Copyright 2020 The Facebook AI Research Team Authors and The 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
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from ..bart.modeling_bart import BartForConditionalGeneration
from .configuration_mbart import MBartConfig
_CONFIG_FOR_DOC = "MBartConfig"
_TOKENIZER_FOR_DOC = "MBartTokenizer"
MBART_PRETRAINED_MODEL_ARCHIVE_LIST = [
"facebook/mbart-large-cc25",
"facebook/mbart-large-en-ro",
# See all multilingual BART models at https://huggingface.co/models?filter=mbart
]
[docs]class MBartForConditionalGeneration(BartForConditionalGeneration):
r"""
This class overrides :class:`~transformers.BartForConditionalGeneration`. Please check the superclass for the
appropriate documentation alongside usage examples.
Examples::
>>> from transformers import MBartForConditionalGeneration, MBartTokenizer
>>> model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-en-ro")
>>> tokenizer = MBartTokenizer.from_pretrained("facebook/mbart-large-en-ro")
>>> article = "UN Chief Says There Is No Military Solution in Syria"
>>> batch = tokenizer.prepare_seq2seq_batch(src_texts=[article], return_tensors="pt")
>>> translated_tokens = model.generate(**batch)
>>> translation = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
>>> assert translation == "Şeful ONU declară că nu există o soluţie militară în Siria"
"""
model_type = "mbart"
config_class = MBartConfig
_keys_to_ignore_on_load_missing = [
"model.encoder.embed_positions.weight",
"model.decoder.embed_positions.weight",
]
_keys_to_ignore_on_save = [
"model.encoder.embed_positions.weight",
"model.decoder.embed_positions.weight",
]