简体中文 | [English] (./README_en.md) # PaddleNLP ![License](https://img.shields.io/badge/license-Apache%202-red.svg) ![python version](https://img.shields.io/badge/python-3.6+-orange.svg) ![support os](https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-yellow.svg) ## Introduction PaddleNLP aims to accelerate NLP applications through powerful model zoo, easy-to-use API with detailed tutorials, It's also the NLP best practice for PaddlePaddle 2.0 API system. **This project is still UNDER ACTIVE DEVELOPMENT.** ## Features * **Rich and Powerful Model Zoo** - Our Model Zoo covers mainstream NLP applications, including Lexical Analysis, Syntactic Parsing, Machine Translation, Text Classification, Text Generation, Text Matching, General Dialogue and Question Answering etc. * **Easy-to-use API** - The API is fully integrated with PaddlePaddle high-level API system. It minimizes the number of user actions required for common use cases like data loading, text pre-processing, training and evaluation. which enables you to deal with text problems more productively. * **High Performance and Large-scale Training** - We provide a highly optimized ditributed training implementation for BERT with Fleet API, it can fully utilize GPU clusters for large-scale model pre-training. Please refer to our [benchmark](./benchmark/bert) for more information. * **Detailed Tutorials and Industrial Practices** - We offers detailed and interactable notebook tutorials to show you the best practices of PaddlePaddle 2.0. ## Installation ### Prerequisites * python >= 3.6 * paddlepaddle >= 2.0.0-rc1 ``` pip install paddlenlp>=2.0.0a ``` ## Quick Start ### Quick Dataset Loading ```python from paddlenlp.datasets import ChnSentiCrop train_ds, test_ds = ChnSentiCorp.get_datasets(['train','test']) ``` ### Chinese Text Emebdding Loading ```python from paddlenlp.embeddings import TokenEmbedding wordemb = TokenEmbedding("w2v.baidu_encyclopedia.target.word-word.dim300") print(wordemb.cosine_sim("国王", "王后")) >>> 0.63395125 wordemb.cosine_sim("艺术", "火车") >>> 0.14792643 ``` ### One-Line Classical Model Building ```python from paddlenlp.models import Ernie ernie = Ernie(Ernie.Task.SeqCls) ernie.forward(input_ids, segment_ids) ``` ### Rich Chinsese Pre-trained Models ```python from paddlenlp.transformers import ErnieModel, BertModel, RobertaModel, ElectraModel ernie = ErnieModel.from_pretrained('ernie-1.0') bert = BertModel.from_pretrained('bert-wwm-chinese') roberta = RobertaModel.from_pretrained('roberta-wwm-ext') electra = ElectraModel.from_pretrained('chinese-electra-small') ``` For more pretrained model selection, please refer to [PretrainedModels](./paddlenlp/transformers/README.md) ## API Usage * [Transformer API](./docs/transformers.md) * [Dataset API](./docs/datasets.md) * [Embedding API](./docs/embeddings.md) * [Metrics API](./docs/embeddings.md) * [Models API](./docs/models.md) ## Tutorials Please refer to our official AI Studio account for more interactive tutorials: [PaddleNLP on AI Studio](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995) ## Community * SIG for Pretrained Model Contribution * SIG for Dataset Integration * SIG for Tutorial Writing ## License PaddleNLP is provided under the [Apache-2.0 License](./LICENSE).