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* Add the pre-trained BARTpho model * Add the pre-trained BARTpho model * Add the pre-trained BARTpho model * Fix incorrectly sorted and/or formatted imports * Fix incorrectly sorted and/or formatted style * Fix check_dummies * Fix check_dummies * Fix check_dummies * Update docs/source/model_doc/bartpho.rst Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update src/transformers/models/bartpho/__init__.py Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update src/transformers/models/bartpho/tokenization_bartpho.py Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update tests/test_tokenization_bartpho.py Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update src/transformers/models/bartpho/tokenization_bartpho.py Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update tests/test_tokenization_bartpho.py Co-authored-by: Suraj Patil <surajp815@gmail.com> * Update docs/source/model_doc/bartpho.rst Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update docs/source/model_doc/bartpho.rst Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/models/bartpho/__init__.py Co-authored-by: Suraj Patil <surajp815@gmail.com> * Add the pre-trained BARTpho model * Add Tips section in doc and details of monolingual_vocab_file * Fix conflicts * Add another tip related to monolingual_vocab_file * Readd dependency_versions_table.py * Handle failing checks * Remove test_list.txt * Remove md5sum.saved * Revise Readme.md Co-authored-by: Suraj Patil <surajp815@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
61 lines
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61 lines
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..
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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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PhoBERT
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-----------------------------------------------------------------------------------------------------------------------
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Overview
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The PhoBERT model was proposed in `PhoBERT: Pre-trained language models for Vietnamese
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<https://www.aclweb.org/anthology/2020.findings-emnlp.92.pdf>`__ by Dat Quoc Nguyen, Anh Tuan Nguyen.
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The abstract from the paper is the following:
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*We present PhoBERT with two versions, PhoBERT-base and PhoBERT-large, the first public large-scale monolingual
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language models pre-trained for Vietnamese. Experimental results show that PhoBERT consistently outperforms the recent
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best pre-trained multilingual model XLM-R (Conneau et al., 2020) and improves the state-of-the-art in multiple
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Vietnamese-specific NLP tasks including Part-of-speech tagging, Dependency parsing, Named-entity recognition and
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Natural language inference.*
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Example of use:
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.. code-block::
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>>> import torch
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>>> from transformers import AutoModel, AutoTokenizer
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>>> phobert = AutoModel.from_pretrained("vinai/phobert-base")
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>>> tokenizer = AutoTokenizer.from_pretrained("vinai/phobert-base")
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>>> # INPUT TEXT MUST BE ALREADY WORD-SEGMENTED!
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>>> line = "Tôi là sinh_viên trường đại_học Công_nghệ ."
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>>> input_ids = torch.tensor([tokenizer.encode(line)])
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>>> with torch.no_grad():
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... features = phobert(input_ids) # Models outputs are now tuples
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>>> # With TensorFlow 2.0+:
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>>> # from transformers import TFAutoModel
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>>> # phobert = TFAutoModel.from_pretrained("vinai/phobert-base")
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This model was contributed by `dqnguyen <https://huggingface.co/dqnguyen>`__. The original code can be found `here
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<https://github.com/VinAIResearch/PhoBERT>`__.
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PhobertTokenizer
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.PhobertTokenizer
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:members:
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