97 lines
3.5 KiB
Markdown
97 lines
3.5 KiB
Markdown
<!--Copyright 2022 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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# Nezha
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<Tip warning={true}>
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This model is in maintenance mode only, we don't accept any new PRs changing its code.
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If you run into any issues running this model, please reinstall the last version that supported this model: v4.40.2.
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You can do so by running the following command: `pip install -U transformers==4.40.2`.
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</Tip>
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## Overview
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The Nezha model was proposed in [NEZHA: Neural Contextualized Representation for Chinese Language Understanding](https://arxiv.org/abs/1909.00204) by Junqiu Wei et al.
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The abstract from the paper is the following:
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*The pre-trained language models have achieved great successes in various natural language understanding (NLU) tasks
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due to its capacity to capture the deep contextualized information in text by pre-training on large-scale corpora.
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In this technical report, we present our practice of pre-training language models named NEZHA (NEural contextualiZed
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representation for CHinese lAnguage understanding) on Chinese corpora and finetuning for the Chinese NLU tasks.
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The current version of NEZHA is based on BERT with a collection of proven improvements, which include Functional
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Relative Positional Encoding as an effective positional encoding scheme, Whole Word Masking strategy,
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Mixed Precision Training and the LAMB Optimizer in training the models. The experimental results show that NEZHA
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achieves the state-of-the-art performances when finetuned on several representative Chinese tasks, including
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named entity recognition (People's Daily NER), sentence matching (LCQMC), Chinese sentiment classification (ChnSenti)
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and natural language inference (XNLI).*
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This model was contributed by [sijunhe](https://huggingface.co/sijunhe). The original code can be found [here](https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/NEZHA-PyTorch).
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## Resources
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- [Text classification task guide](../tasks/sequence_classification)
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- [Token classification task guide](../tasks/token_classification)
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- [Question answering task guide](../tasks/question_answering)
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- [Masked language modeling task guide](../tasks/masked_language_modeling)
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- [Multiple choice task guide](../tasks/multiple_choice)
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## NezhaConfig
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[[autodoc]] NezhaConfig
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## NezhaModel
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[[autodoc]] NezhaModel
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- forward
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## NezhaForPreTraining
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[[autodoc]] NezhaForPreTraining
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- forward
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## NezhaForMaskedLM
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[[autodoc]] NezhaForMaskedLM
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- forward
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## NezhaForNextSentencePrediction
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[[autodoc]] NezhaForNextSentencePrediction
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- forward
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## NezhaForSequenceClassification
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[[autodoc]] NezhaForSequenceClassification
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- forward
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## NezhaForMultipleChoice
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[[autodoc]] NezhaForMultipleChoice
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- forward
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## NezhaForTokenClassification
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[[autodoc]] NezhaForTokenClassification
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- forward
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## NezhaForQuestionAnswering
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[[autodoc]] NezhaForQuestionAnswering
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- forward
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