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+/paddlenlp-2.5.2.tar.gz
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+%global _empty_manifest_terminate_build 0
+Name:		python-paddlenlp
+Version:	2.5.2
+Release:	1
+Summary:	Easy-to-use and powerful NLP library with Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including Neural Search, Question Answering, Information Extraction and Sentiment Analysis end-to-end system.
+License:	Apache 2.0
+URL:		https://github.com/PaddlePaddle/PaddleNLP
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/ac/30/204ab2e0e01222060db5684041d5c4a73dec0adb622e3397f88d15b38f94/paddlenlp-2.5.2.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-jieba
+Requires:	python3-colorlog
+Requires:	python3-colorama
+Requires:	python3-seqeval
+Requires:	python3-dill
+Requires:	python3-multiprocess
+Requires:	python3-datasets
+Requires:	python3-tqdm
+Requires:	python3-paddlefsl
+Requires:	python3-sentencepiece
+Requires:	python3-huggingface-hub
+Requires:	python3-paddle2onnx
+Requires:	python3-Flask-Babel
+Requires:	python3-visualdl
+Requires:	python3-fastapi
+Requires:	python3-uvicorn
+Requires:	python3-typer
+Requires:	python3-rich
+Requires:	python3-ray[tune]
+Requires:	python3-hyperopt
+Requires:	python3-parameterized
+Requires:	python3-sentencepiece
+Requires:	python3-regex
+Requires:	python3-torch
+Requires:	python3-transformers
+Requires:	python3-fast-tokenizer-python
+Requires:	python3-jinja2
+Requires:	python3-sphinx
+Requires:	python3-sphinx-rtd-theme
+Requires:	python3-readthedocs-sphinx-search
+Requires:	python3-Markdown
+Requires:	python3-sphinx-copybutton
+Requires:	python3-sphinx-markdown-tables
+Requires:	python3-paddlepaddle
+Requires:	python3-ray[tune]
+Requires:	python3-hyperopt
+Requires:	python3-jinja2
+Requires:	python3-sphinx
+Requires:	python3-sphinx-rtd-theme
+Requires:	python3-readthedocs-sphinx-search
+Requires:	python3-Markdown
+Requires:	python3-sphinx-copybutton
+Requires:	python3-sphinx-markdown-tables
+Requires:	python3-paddlepaddle
+Requires:	python3-parameterized
+Requires:	python3-sentencepiece
+Requires:	python3-regex
+Requires:	python3-torch
+Requires:	python3-transformers
+Requires:	python3-fast-tokenizer-python
+
+%description
+<p align="center">
+    <a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleNLP?color=ffa"></a>
+    <a href=""><img src="https://img.shields.io/badge/python-3.6.2+-aff.svg"></a>
+    <a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/PaddleNLP?color=9ea"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/PaddleNLP?color=3af"></a>
+    <a href="https://pypi.org/project/paddlenlp/"><img src="https://img.shields.io/pypi/dm/paddlenlp?color=9cf"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/PaddleNLP?color=9cc"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleNLP?color=ccf"></a>
+</p>
+<h4 align="center">
+  <a href=#features> Features </a> |
+  <a href=#installation> Installation </a> |
+  <a href=#quick-start> Quick Start </a> |
+  <a href=#api-reference> API Reference </a> |
+  <a href=#community> Community </a>
+</h4>
+**PaddleNLP** is an *easy-to-use* and *powerful* NLP library with **Awesome** pre-trained model zoo, supporting wide-range of NLP tasks from research to industrial applications.
+## News 📢
+* 🔥 **Latest Features**
+  * 📃 Release **[UIE-X](./applications/information_extraction)**, an universal information extraction model that supports both document and text inputs.
+  * ❣️Release  **[Opinion Mining and Sentiment Analysis Models](./applications/sentiment_analysis/unified_sentiment_extraction)** based on UIE,  including abilities of sentence-level and aspect-based sentiment classification, attribute extraction,  opinion extraction,  attribute aggregation and implicit opinion extraction.
+* **2022.9.6 [PaddleNLPv2.4](https://github.com/PaddlePaddle/PaddleNLP/releases/tag/v2.4.0) Released!**
+  * 💎 NLP Tools: Released **[Pipelines](./pipelines)** which supports turn-key construction of search engine and question answering systems. It features a flexible design that is applicable for all kinds of NLP systems so you can build end-to-end NLP pipelines like Legos!
+  * 🔨 Industrial application: Release **[Complete Solution of Text Classification](./applications/text_classification)** covering various scenarios of text classification: multi-class, multi-label and hierarchical, it also supports **few-shot learning** and the training and optimization of **TrustAI**. Upgrade for [**UIE**](./model_zoo/uie) and release **UIE-M**, support both Chinese and English information extraction in a single model; release the data distillation solution for UIE to break the bottleneck of time-consuming of inference.
+  * 🍭 AIGC: Release code generation SOTA model [**CodeGen**](./examples/code_generation/codegen) that supports  multiple programming languages code generation. Integrate [**Text to Image Model**](https://github.com/PaddlePaddle/PaddleNLP/blob/develop/docs/model_zoo/taskflow.md#%E6%96%87%E5%9B%BE%E7%94%9F%E6%88%90) DALL·E Mini, Disco Diffusion, Stable Diffusion, let's play and have some fun!
+  * 💪 Framework upgrade: Release [**Auto Model Compression API**](./docs/compression.md), supports for pruning and quantization automatically, lower the barriers of model compression; Release [**Few-shot Prompt**](./applications/text_classification/multi_class/few-shot), includes the algorithms such as PET, P-Tuning and RGL.
+## Features
+#### <a href=#out-of-box-nlp-toolset> 📦 Out-of-Box NLP Toolset </a>
+#### <a href=#awesome-chinese-model-zoo> 🤗 Awesome Chinese Model Zoo </a>
+#### <a href=#industrial-end-to-end-system> 🎛️ Industrial End-to-end System </a>
+#### <a href=#high-performance-distributed-training-and-inference> 🚀 High Performance Distributed Training and Inference </a>
+### Out-of-Box NLP Toolset
+Taskflow aims to provide off-the-shelf NLP pre-built task covering NLU and NLG technique, in the meanwhile with extreamly fast infernece satisfying industrial scenario.
+![taskflow1](https://user-images.githubusercontent.com/11793384/159693816-fda35221-9751-43bb-b05c-7fc77571dd76.gif)
+For more usage please refer to [Taskflow Docs](./docs/model_zoo/taskflow.md).
+### Awesome Chinese Model Zoo
+#### 🀄 Comprehensive Chinese Transformer Models
+We provide **45+** network architectures and over **500+** pretrained models. Not only includes all the SOTA model like ERNIE, PLATO and SKEP released by Baidu, but also integrates most of the high-quality Chinese pretrained model developed by other organizations. Use `AutoModel` API to **⚡SUPER FAST⚡** download pretrained models of different architecture. We welcome all developers to contribute your Transformer models to PaddleNLP!
+```python
+from paddlenlp.transformers import *
+ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+bert = AutoModel.from_pretrained('bert-wwm-chinese')
+albert = AutoModel.from_pretrained('albert-chinese-tiny')
+roberta = AutoModel.from_pretrained('roberta-wwm-ext')
+electra = AutoModel.from_pretrained('chinese-electra-small')
+gpt = AutoModelForPretraining.from_pretrained('gpt-cpm-large-cn')
+```
+Due to the computation limitation, you can use the ERNIE-Tiny light models to accelerate the deployment of pretrained models.
+```python
+# 6L768H
+ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+# 6L384H
+ernie = AutoModel.from_pretrained('ernie-3.0-mini-zh')
+# 4L384H
+ernie = AutoModel.from_pretrained('ernie-3.0-micro-zh')
+# 4L312H
+ernie = AutoModel.from_pretrained('ernie-3.0-nano-zh')
+```
+Unified API experience for NLP task like semantic representation, text classification, sentence matching, sequence labeling, question answering, etc.
+```python
+import paddle
+from paddlenlp.transformers import *
+tokenizer = AutoTokenizer.from_pretrained('ernie-3.0-medium-zh')
+text = tokenizer('natural language processing')
+# Semantic Representation
+model = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+sequence_output, pooled_output = model(input_ids=paddle.to_tensor([text['input_ids']]))
+# Text Classificaiton and Matching
+model = AutoModelForSequenceClassification.from_pretrained('ernie-3.0-medium-zh')
+# Sequence Labeling
+model = AutoModelForTokenClassification.from_pretrained('ernie-3.0-medium-zh')
+# Question Answering
+model = AutoModelForQuestionAnswering.from_pretrained('ernie-3.0-medium-zh')
+```
+#### Wide-range NLP Task Support
+PaddleNLP provides rich examples covering mainstream NLP task to help developers accelerate problem solving. You can find our powerful transformer [Model Zoo](./model_zoo), and wide-range NLP application [exmaples](./examples) with detailed instructions.
+Also you can run our interactive [Notebook tutorial](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995) on AI Studio, a powerful platform with **FREE** computing resource.
+<details><summary> PaddleNLP Transformer model summary (<b>click to show details</b>) </summary><div>
+| Model              | Sequence Classification | Token Classification | Question Answering | Text Generation | Multiple Choice |
+| :----------------- | ----------------------- | -------------------- | ------------------ | --------------- | --------------- |
+| ALBERT             | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BART               | ✅                       | ✅                    | ✅                  | ✅               | ❌               |
+| BERT               | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BigBird            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BlenderBot         | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| ChineseBERT        | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ConvBERT           | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| CTRL               | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| DistilBERT         | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ELECTRA            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| ERNIE              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| ERNIE-CTM          | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| ERNIE-Doc          | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ERNIE-GEN          | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| ERNIE-Gram         | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ERNIE-M            | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| FNet               | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| Funnel-Transformer | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| GPT                | ✅                       | ✅                    | ❌                  | ✅               | ❌               |
+| LayoutLM           | ✅                       | ✅                    | ❌                  | ❌               | ❌               |
+| LayoutLMv2         | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| LayoutXLM          | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| LUKE               | ❌                       | ✅                    | ✅                  | ❌               | ❌               |
+| mBART              | ✅                       | ❌                    | ✅                  | ❌               | ✅               |
+| MegatronBERT       | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| MobileBERT         | ✅                       | ❌                    | ✅                  | ❌               | ❌               |
+| MPNet              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| NEZHA              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| PP-MiniLM          | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| ProphetNet         | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| Reformer           | ✅                       | ❌                    | ✅                  | ❌               | ❌               |
+| RemBERT            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| RoBERTa            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| RoFormer           | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| SKEP               | ✅                       | ✅                    | ❌                  | ❌               | ❌               |
+| SqueezeBERT        | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| T5                 | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| TinyBERT           | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| UnifiedTransformer | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| XLNet              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+</div></details>
+For more pretrained model usage, please refer to [Transformer API Docs](./docs/model_zoo/index.rst).
+### Industrial End-to-end System
+We provide high value scenarios including information extraction, semantic retrieval, questionn answering high-value.
+For more details industial cases please refer to [Applications](./applications).
+#### 🔍 Neural Search System
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168514909-8817d79a-72c4-4be1-8080-93d1f682bb46.gif" width="400">
+</div>
+For more details please refer to [Neural Search](./applications/neural_search).
+#### ❓ Question Answering System
+We provide question answering pipeline which can support FAQ system, Document-level Visual Question answering system based on [🚀RocketQA](https://github.com/PaddlePaddle/RocketQA).
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168514868-1babe981-c675-4f89-9168-dd0a3eede315.gif" width="400">
+</div>
+For more details please refer to [Question Answering](./applications/question_answering) and [Document VQA](./applications/document_intelligence/doc_vqa).
+#### 💌 Opinion Extraction and Sentiment Analysis
+We build an opinion extraction system for product review and fine-grained sentiment analysis based on [SKEP](https://arxiv.org/abs/2005.05635) Model.
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407260-b7f92800-861c-4207-98f3-2291e0102bbe.png" width="300">
+</div>
+For more details please refer to [Sentiment Analysis](./applications/sentiment_analysis).
+#### 🎙️ Speech Command Analysis
+Integrated ASR Model, Information Extraction, we provide a speech command analysis pipeline that show how to use PaddleNLP and [PaddleSpeech](https://github.com/PaddlePaddle/PaddleSpeech) to solve Speech + NLP real scenarios.
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168412618-04897a47-79c9-4fe7-a054-5dc1f6a1f75c.png" width="500">
+</div>
+For more details please refer to [Speech Command Analysis](./applications/speech_cmd_analysis).
+### High Performance Distributed Training and Inference
+#### ⚡ FastTokenizer: High Performance Text Preprocessing Library
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407921-b4395b1d-44bd-41a0-8c58-923ba2b703ef.png" width="400">
+</div>
+```python
+AutoTokenizer.from_pretrained("ernie-3.0-medium-zh", use_fast=True)
+```
+Set `use_fast=True` to use C++ Tokenizer kernel to achieve 100x faster on text pre-processing. For more usage please refer to [FastTokenizer](./fast_tokenizer).
+#### ⚡ FastGeneration: High Perforance Generation Library
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407831-914dced0-3a5a-40b8-8a65-ec82bf13e53c.gif" width="400">
+</div>
+```python
+model = GPTLMHeadModel.from_pretrained('gpt-cpm-large-cn')
+outputs, _ = model.generate(
+    input_ids=inputs_ids, max_length=10, decode_strategy='greedy_search',
+    use_fast=True)
+```
+Set `use_fast=True` to achieve 5x speedup for Transformer, GPT, BART, PLATO, UniLM text generation. For more usage please refer to [FastGeneration](./fast_generation).
+#### 🚀 Fleet: 4D Hybrid Distributed Training
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168515134-513f13e0-9902-40ef-98fa-528271dcccda.png" width="300">
+</div>
+For more super large-scale model pre-training details please refer to [GPT-3](./examples/language_model/gpt-3).
+## Installation
+### Prerequisites
+* python >= 3.7
+* paddlepaddle >= 2.3
+More information about PaddlePaddle installation please refer to [PaddlePaddle's Website](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/conda/linux-conda.html).
+### Python pip Installation
+```
+pip install --upgrade paddlenlp
+```
+or you can install the latest develop branch code with the following command:
+```shell
+pip install --pre --upgrade paddlenlp -f https://www.paddlepaddle.org.cn/whl/paddlenlp.html
+```
+## Quick Start
+**Taskflow** aims to provide off-the-shelf NLP pre-built task covering NLU and NLG scenario, in the meanwhile with extreamly fast infernece satisfying industrial applications.
+```python
+from paddlenlp import Taskflow
+# Chinese Word Segmentation
+seg = Taskflow("word_segmentation")
+seg("第十四届全运会在西安举办")
+>>> ['第十四届', '全运会', '在', '西安', '举办']
+# POS Tagging
+tag = Taskflow("pos_tagging")
+tag("第十四届全运会在西安举办")
+>>> [('第十四届', 'm'), ('全运会', 'nz'), ('在', 'p'), ('西安', 'LOC'), ('举办', 'v')]
+# Named Entity Recognition
+ner = Taskflow("ner")
+ner("《孤女》是2010年九州出版社出版的小说，作者是余兼羽")
+>>> [('《', 'w'), ('孤女', '作品类_实体'), ('》', 'w'), ('是', '肯定词'), ('2010年', '时间类'), ('九州出版社', '组织机构类'), ('出版', '场景事件'), ('的', '助词'), ('小说', '作品类_概念'), ('，', 'w'), ('作者', '人物类_概念'), ('是', '肯定词'), ('余兼羽', '人物类_实体')]
+# Dependency Parsing
+ddp = Taskflow("dependency_parsing")
+ddp("9月9日上午纳达尔在亚瑟·阿什球场击败俄罗斯球员梅德韦杰夫")
+>>> [{'word': ['9月9日', '上午', '纳达尔', '在', '亚瑟·阿什球场', '击败', '俄罗斯', '球员', '梅德韦杰夫'], 'head': [2, 6, 6, 5, 6, 0, 8, 9, 6], 'deprel': ['ATT', 'ADV', 'SBV', 'MT', 'ADV', 'HED', 'ATT', 'ATT', 'VOB']}]
+# Sentiment Analysis
+senta = Taskflow("sentiment_analysis")
+senta("这个产品用起来真的很流畅，我非常喜欢")
+>>> [{'text': '这个产品用起来真的很流畅，我非常喜欢', 'label': 'positive', 'score': 0.9938690066337585}]
+```
+## API Reference
+- Support [LUGE](https://www.luge.ai/) dataset loading and compatible with Hugging Face [Datasets](https://huggingface.co/datasets). For more details please refer to [Dataset API](https://paddlenlp.readthedocs.io/zh/latest/data_prepare/dataset_list.html).
+- Using Hugging Face style API to load 500+ selected transformer models and download with fast speed. For more information please refer to [Transformers API](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/index.html).
+- One-line of code to load pre-trained word embedding. For more usage please refer to [Embedding API](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/embeddings.html).
+Please find all PaddleNLP API Reference from our [readthedocs](https://paddlenlp.readthedocs.io/).
+## Community
+### Slack
+To connect with other users and contributors, welcome to join our [Slack channel](https://paddlenlp.slack.com/).
+### WeChat
+Scan the QR code below with your Wechat⬇️. You can access to official technical exchange group. Look forward to your participation.
+<div align="center">
+<img src="https://user-images.githubusercontent.com/11793384/212060369-4642d16e-f0ad-4359-aa57-b8303042f9c1.jpg" width="150" height="150" />
+</div>
+## Citation
+If you find PaddleNLP useful in your research, please consider cite
+```
+@misc{=paddlenlp,
+    title={PaddleNLP: An Easy-to-use and High Performance NLP Library},
+    author={PaddleNLP Contributors},
+    howpublished = {\url{https://github.com/PaddlePaddle/PaddleNLP}},
+    year={2021}
+}
+```
+## Acknowledge
+We have borrowed from Hugging Face's [Transformers](https://github.com/huggingface/transformers)🤗 excellent design on pretrained models usage, and we would like to express our gratitude to the authors of Hugging Face and its open source community.
+## License
+PaddleNLP is provided under the [Apache-2.0 License](./LICENSE).
+
+%package -n python3-paddlenlp
+Summary:	Easy-to-use and powerful NLP library with Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including Neural Search, Question Answering, Information Extraction and Sentiment Analysis end-to-end system.
+Provides:	python-paddlenlp
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-paddlenlp
+<p align="center">
+    <a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleNLP?color=ffa"></a>
+    <a href=""><img src="https://img.shields.io/badge/python-3.6.2+-aff.svg"></a>
+    <a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/PaddleNLP?color=9ea"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/PaddleNLP?color=3af"></a>
+    <a href="https://pypi.org/project/paddlenlp/"><img src="https://img.shields.io/pypi/dm/paddlenlp?color=9cf"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/PaddleNLP?color=9cc"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleNLP?color=ccf"></a>
+</p>
+<h4 align="center">
+  <a href=#features> Features </a> |
+  <a href=#installation> Installation </a> |
+  <a href=#quick-start> Quick Start </a> |
+  <a href=#api-reference> API Reference </a> |
+  <a href=#community> Community </a>
+</h4>
+**PaddleNLP** is an *easy-to-use* and *powerful* NLP library with **Awesome** pre-trained model zoo, supporting wide-range of NLP tasks from research to industrial applications.
+## News 📢
+* 🔥 **Latest Features**
+  * 📃 Release **[UIE-X](./applications/information_extraction)**, an universal information extraction model that supports both document and text inputs.
+  * ❣️Release  **[Opinion Mining and Sentiment Analysis Models](./applications/sentiment_analysis/unified_sentiment_extraction)** based on UIE,  including abilities of sentence-level and aspect-based sentiment classification, attribute extraction,  opinion extraction,  attribute aggregation and implicit opinion extraction.
+* **2022.9.6 [PaddleNLPv2.4](https://github.com/PaddlePaddle/PaddleNLP/releases/tag/v2.4.0) Released!**
+  * 💎 NLP Tools: Released **[Pipelines](./pipelines)** which supports turn-key construction of search engine and question answering systems. It features a flexible design that is applicable for all kinds of NLP systems so you can build end-to-end NLP pipelines like Legos!
+  * 🔨 Industrial application: Release **[Complete Solution of Text Classification](./applications/text_classification)** covering various scenarios of text classification: multi-class, multi-label and hierarchical, it also supports **few-shot learning** and the training and optimization of **TrustAI**. Upgrade for [**UIE**](./model_zoo/uie) and release **UIE-M**, support both Chinese and English information extraction in a single model; release the data distillation solution for UIE to break the bottleneck of time-consuming of inference.
+  * 🍭 AIGC: Release code generation SOTA model [**CodeGen**](./examples/code_generation/codegen) that supports  multiple programming languages code generation. Integrate [**Text to Image Model**](https://github.com/PaddlePaddle/PaddleNLP/blob/develop/docs/model_zoo/taskflow.md#%E6%96%87%E5%9B%BE%E7%94%9F%E6%88%90) DALL·E Mini, Disco Diffusion, Stable Diffusion, let's play and have some fun!
+  * 💪 Framework upgrade: Release [**Auto Model Compression API**](./docs/compression.md), supports for pruning and quantization automatically, lower the barriers of model compression; Release [**Few-shot Prompt**](./applications/text_classification/multi_class/few-shot), includes the algorithms such as PET, P-Tuning and RGL.
+## Features
+#### <a href=#out-of-box-nlp-toolset> 📦 Out-of-Box NLP Toolset </a>
+#### <a href=#awesome-chinese-model-zoo> 🤗 Awesome Chinese Model Zoo </a>
+#### <a href=#industrial-end-to-end-system> 🎛️ Industrial End-to-end System </a>
+#### <a href=#high-performance-distributed-training-and-inference> 🚀 High Performance Distributed Training and Inference </a>
+### Out-of-Box NLP Toolset
+Taskflow aims to provide off-the-shelf NLP pre-built task covering NLU and NLG technique, in the meanwhile with extreamly fast infernece satisfying industrial scenario.
+![taskflow1](https://user-images.githubusercontent.com/11793384/159693816-fda35221-9751-43bb-b05c-7fc77571dd76.gif)
+For more usage please refer to [Taskflow Docs](./docs/model_zoo/taskflow.md).
+### Awesome Chinese Model Zoo
+#### 🀄 Comprehensive Chinese Transformer Models
+We provide **45+** network architectures and over **500+** pretrained models. Not only includes all the SOTA model like ERNIE, PLATO and SKEP released by Baidu, but also integrates most of the high-quality Chinese pretrained model developed by other organizations. Use `AutoModel` API to **⚡SUPER FAST⚡** download pretrained models of different architecture. We welcome all developers to contribute your Transformer models to PaddleNLP!
+```python
+from paddlenlp.transformers import *
+ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+bert = AutoModel.from_pretrained('bert-wwm-chinese')
+albert = AutoModel.from_pretrained('albert-chinese-tiny')
+roberta = AutoModel.from_pretrained('roberta-wwm-ext')
+electra = AutoModel.from_pretrained('chinese-electra-small')
+gpt = AutoModelForPretraining.from_pretrained('gpt-cpm-large-cn')
+```
+Due to the computation limitation, you can use the ERNIE-Tiny light models to accelerate the deployment of pretrained models.
+```python
+# 6L768H
+ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+# 6L384H
+ernie = AutoModel.from_pretrained('ernie-3.0-mini-zh')
+# 4L384H
+ernie = AutoModel.from_pretrained('ernie-3.0-micro-zh')
+# 4L312H
+ernie = AutoModel.from_pretrained('ernie-3.0-nano-zh')
+```
+Unified API experience for NLP task like semantic representation, text classification, sentence matching, sequence labeling, question answering, etc.
+```python
+import paddle
+from paddlenlp.transformers import *
+tokenizer = AutoTokenizer.from_pretrained('ernie-3.0-medium-zh')
+text = tokenizer('natural language processing')
+# Semantic Representation
+model = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+sequence_output, pooled_output = model(input_ids=paddle.to_tensor([text['input_ids']]))
+# Text Classificaiton and Matching
+model = AutoModelForSequenceClassification.from_pretrained('ernie-3.0-medium-zh')
+# Sequence Labeling
+model = AutoModelForTokenClassification.from_pretrained('ernie-3.0-medium-zh')
+# Question Answering
+model = AutoModelForQuestionAnswering.from_pretrained('ernie-3.0-medium-zh')
+```
+#### Wide-range NLP Task Support
+PaddleNLP provides rich examples covering mainstream NLP task to help developers accelerate problem solving. You can find our powerful transformer [Model Zoo](./model_zoo), and wide-range NLP application [exmaples](./examples) with detailed instructions.
+Also you can run our interactive [Notebook tutorial](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995) on AI Studio, a powerful platform with **FREE** computing resource.
+<details><summary> PaddleNLP Transformer model summary (<b>click to show details</b>) </summary><div>
+| Model              | Sequence Classification | Token Classification | Question Answering | Text Generation | Multiple Choice |
+| :----------------- | ----------------------- | -------------------- | ------------------ | --------------- | --------------- |
+| ALBERT             | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BART               | ✅                       | ✅                    | ✅                  | ✅               | ❌               |
+| BERT               | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BigBird            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BlenderBot         | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| ChineseBERT        | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ConvBERT           | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| CTRL               | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| DistilBERT         | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ELECTRA            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| ERNIE              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| ERNIE-CTM          | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| ERNIE-Doc          | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ERNIE-GEN          | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| ERNIE-Gram         | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ERNIE-M            | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| FNet               | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| Funnel-Transformer | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| GPT                | ✅                       | ✅                    | ❌                  | ✅               | ❌               |
+| LayoutLM           | ✅                       | ✅                    | ❌                  | ❌               | ❌               |
+| LayoutLMv2         | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| LayoutXLM          | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| LUKE               | ❌                       | ✅                    | ✅                  | ❌               | ❌               |
+| mBART              | ✅                       | ❌                    | ✅                  | ❌               | ✅               |
+| MegatronBERT       | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| MobileBERT         | ✅                       | ❌                    | ✅                  | ❌               | ❌               |
+| MPNet              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| NEZHA              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| PP-MiniLM          | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| ProphetNet         | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| Reformer           | ✅                       | ❌                    | ✅                  | ❌               | ❌               |
+| RemBERT            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| RoBERTa            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| RoFormer           | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| SKEP               | ✅                       | ✅                    | ❌                  | ❌               | ❌               |
+| SqueezeBERT        | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| T5                 | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| TinyBERT           | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| UnifiedTransformer | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| XLNet              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+</div></details>
+For more pretrained model usage, please refer to [Transformer API Docs](./docs/model_zoo/index.rst).
+### Industrial End-to-end System
+We provide high value scenarios including information extraction, semantic retrieval, questionn answering high-value.
+For more details industial cases please refer to [Applications](./applications).
+#### 🔍 Neural Search System
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168514909-8817d79a-72c4-4be1-8080-93d1f682bb46.gif" width="400">
+</div>
+For more details please refer to [Neural Search](./applications/neural_search).
+#### ❓ Question Answering System
+We provide question answering pipeline which can support FAQ system, Document-level Visual Question answering system based on [🚀RocketQA](https://github.com/PaddlePaddle/RocketQA).
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168514868-1babe981-c675-4f89-9168-dd0a3eede315.gif" width="400">
+</div>
+For more details please refer to [Question Answering](./applications/question_answering) and [Document VQA](./applications/document_intelligence/doc_vqa).
+#### 💌 Opinion Extraction and Sentiment Analysis
+We build an opinion extraction system for product review and fine-grained sentiment analysis based on [SKEP](https://arxiv.org/abs/2005.05635) Model.
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407260-b7f92800-861c-4207-98f3-2291e0102bbe.png" width="300">
+</div>
+For more details please refer to [Sentiment Analysis](./applications/sentiment_analysis).
+#### 🎙️ Speech Command Analysis
+Integrated ASR Model, Information Extraction, we provide a speech command analysis pipeline that show how to use PaddleNLP and [PaddleSpeech](https://github.com/PaddlePaddle/PaddleSpeech) to solve Speech + NLP real scenarios.
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168412618-04897a47-79c9-4fe7-a054-5dc1f6a1f75c.png" width="500">
+</div>
+For more details please refer to [Speech Command Analysis](./applications/speech_cmd_analysis).
+### High Performance Distributed Training and Inference
+#### ⚡ FastTokenizer: High Performance Text Preprocessing Library
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407921-b4395b1d-44bd-41a0-8c58-923ba2b703ef.png" width="400">
+</div>
+```python
+AutoTokenizer.from_pretrained("ernie-3.0-medium-zh", use_fast=True)
+```
+Set `use_fast=True` to use C++ Tokenizer kernel to achieve 100x faster on text pre-processing. For more usage please refer to [FastTokenizer](./fast_tokenizer).
+#### ⚡ FastGeneration: High Perforance Generation Library
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407831-914dced0-3a5a-40b8-8a65-ec82bf13e53c.gif" width="400">
+</div>
+```python
+model = GPTLMHeadModel.from_pretrained('gpt-cpm-large-cn')
+outputs, _ = model.generate(
+    input_ids=inputs_ids, max_length=10, decode_strategy='greedy_search',
+    use_fast=True)
+```
+Set `use_fast=True` to achieve 5x speedup for Transformer, GPT, BART, PLATO, UniLM text generation. For more usage please refer to [FastGeneration](./fast_generation).
+#### 🚀 Fleet: 4D Hybrid Distributed Training
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168515134-513f13e0-9902-40ef-98fa-528271dcccda.png" width="300">
+</div>
+For more super large-scale model pre-training details please refer to [GPT-3](./examples/language_model/gpt-3).
+## Installation
+### Prerequisites
+* python >= 3.7
+* paddlepaddle >= 2.3
+More information about PaddlePaddle installation please refer to [PaddlePaddle's Website](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/conda/linux-conda.html).
+### Python pip Installation
+```
+pip install --upgrade paddlenlp
+```
+or you can install the latest develop branch code with the following command:
+```shell
+pip install --pre --upgrade paddlenlp -f https://www.paddlepaddle.org.cn/whl/paddlenlp.html
+```
+## Quick Start
+**Taskflow** aims to provide off-the-shelf NLP pre-built task covering NLU and NLG scenario, in the meanwhile with extreamly fast infernece satisfying industrial applications.
+```python
+from paddlenlp import Taskflow
+# Chinese Word Segmentation
+seg = Taskflow("word_segmentation")
+seg("第十四届全运会在西安举办")
+>>> ['第十四届', '全运会', '在', '西安', '举办']
+# POS Tagging
+tag = Taskflow("pos_tagging")
+tag("第十四届全运会在西安举办")
+>>> [('第十四届', 'm'), ('全运会', 'nz'), ('在', 'p'), ('西安', 'LOC'), ('举办', 'v')]
+# Named Entity Recognition
+ner = Taskflow("ner")
+ner("《孤女》是2010年九州出版社出版的小说，作者是余兼羽")
+>>> [('《', 'w'), ('孤女', '作品类_实体'), ('》', 'w'), ('是', '肯定词'), ('2010年', '时间类'), ('九州出版社', '组织机构类'), ('出版', '场景事件'), ('的', '助词'), ('小说', '作品类_概念'), ('，', 'w'), ('作者', '人物类_概念'), ('是', '肯定词'), ('余兼羽', '人物类_实体')]
+# Dependency Parsing
+ddp = Taskflow("dependency_parsing")
+ddp("9月9日上午纳达尔在亚瑟·阿什球场击败俄罗斯球员梅德韦杰夫")
+>>> [{'word': ['9月9日', '上午', '纳达尔', '在', '亚瑟·阿什球场', '击败', '俄罗斯', '球员', '梅德韦杰夫'], 'head': [2, 6, 6, 5, 6, 0, 8, 9, 6], 'deprel': ['ATT', 'ADV', 'SBV', 'MT', 'ADV', 'HED', 'ATT', 'ATT', 'VOB']}]
+# Sentiment Analysis
+senta = Taskflow("sentiment_analysis")
+senta("这个产品用起来真的很流畅，我非常喜欢")
+>>> [{'text': '这个产品用起来真的很流畅，我非常喜欢', 'label': 'positive', 'score': 0.9938690066337585}]
+```
+## API Reference
+- Support [LUGE](https://www.luge.ai/) dataset loading and compatible with Hugging Face [Datasets](https://huggingface.co/datasets). For more details please refer to [Dataset API](https://paddlenlp.readthedocs.io/zh/latest/data_prepare/dataset_list.html).
+- Using Hugging Face style API to load 500+ selected transformer models and download with fast speed. For more information please refer to [Transformers API](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/index.html).
+- One-line of code to load pre-trained word embedding. For more usage please refer to [Embedding API](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/embeddings.html).
+Please find all PaddleNLP API Reference from our [readthedocs](https://paddlenlp.readthedocs.io/).
+## Community
+### Slack
+To connect with other users and contributors, welcome to join our [Slack channel](https://paddlenlp.slack.com/).
+### WeChat
+Scan the QR code below with your Wechat⬇️. You can access to official technical exchange group. Look forward to your participation.
+<div align="center">
+<img src="https://user-images.githubusercontent.com/11793384/212060369-4642d16e-f0ad-4359-aa57-b8303042f9c1.jpg" width="150" height="150" />
+</div>
+## Citation
+If you find PaddleNLP useful in your research, please consider cite
+```
+@misc{=paddlenlp,
+    title={PaddleNLP: An Easy-to-use and High Performance NLP Library},
+    author={PaddleNLP Contributors},
+    howpublished = {\url{https://github.com/PaddlePaddle/PaddleNLP}},
+    year={2021}
+}
+```
+## Acknowledge
+We have borrowed from Hugging Face's [Transformers](https://github.com/huggingface/transformers)🤗 excellent design on pretrained models usage, and we would like to express our gratitude to the authors of Hugging Face and its open source community.
+## License
+PaddleNLP is provided under the [Apache-2.0 License](./LICENSE).
+
+%package help
+Summary:	Development documents and examples for paddlenlp
+Provides:	python3-paddlenlp-doc
+%description help
+<p align="center">
+    <a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-dfd.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleNLP?color=ffa"></a>
+    <a href=""><img src="https://img.shields.io/badge/python-3.6.2+-aff.svg"></a>
+    <a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/PaddleNLP?color=9ea"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/PaddleNLP?color=3af"></a>
+    <a href="https://pypi.org/project/paddlenlp/"><img src="https://img.shields.io/pypi/dm/paddlenlp?color=9cf"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/PaddleNLP?color=9cc"></a>
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleNLP?color=ccf"></a>
+</p>
+<h4 align="center">
+  <a href=#features> Features </a> |
+  <a href=#installation> Installation </a> |
+  <a href=#quick-start> Quick Start </a> |
+  <a href=#api-reference> API Reference </a> |
+  <a href=#community> Community </a>
+</h4>
+**PaddleNLP** is an *easy-to-use* and *powerful* NLP library with **Awesome** pre-trained model zoo, supporting wide-range of NLP tasks from research to industrial applications.
+## News 📢
+* 🔥 **Latest Features**
+  * 📃 Release **[UIE-X](./applications/information_extraction)**, an universal information extraction model that supports both document and text inputs.
+  * ❣️Release  **[Opinion Mining and Sentiment Analysis Models](./applications/sentiment_analysis/unified_sentiment_extraction)** based on UIE,  including abilities of sentence-level and aspect-based sentiment classification, attribute extraction,  opinion extraction,  attribute aggregation and implicit opinion extraction.
+* **2022.9.6 [PaddleNLPv2.4](https://github.com/PaddlePaddle/PaddleNLP/releases/tag/v2.4.0) Released!**
+  * 💎 NLP Tools: Released **[Pipelines](./pipelines)** which supports turn-key construction of search engine and question answering systems. It features a flexible design that is applicable for all kinds of NLP systems so you can build end-to-end NLP pipelines like Legos!
+  * 🔨 Industrial application: Release **[Complete Solution of Text Classification](./applications/text_classification)** covering various scenarios of text classification: multi-class, multi-label and hierarchical, it also supports **few-shot learning** and the training and optimization of **TrustAI**. Upgrade for [**UIE**](./model_zoo/uie) and release **UIE-M**, support both Chinese and English information extraction in a single model; release the data distillation solution for UIE to break the bottleneck of time-consuming of inference.
+  * 🍭 AIGC: Release code generation SOTA model [**CodeGen**](./examples/code_generation/codegen) that supports  multiple programming languages code generation. Integrate [**Text to Image Model**](https://github.com/PaddlePaddle/PaddleNLP/blob/develop/docs/model_zoo/taskflow.md#%E6%96%87%E5%9B%BE%E7%94%9F%E6%88%90) DALL·E Mini, Disco Diffusion, Stable Diffusion, let's play and have some fun!
+  * 💪 Framework upgrade: Release [**Auto Model Compression API**](./docs/compression.md), supports for pruning and quantization automatically, lower the barriers of model compression; Release [**Few-shot Prompt**](./applications/text_classification/multi_class/few-shot), includes the algorithms such as PET, P-Tuning and RGL.
+## Features
+#### <a href=#out-of-box-nlp-toolset> 📦 Out-of-Box NLP Toolset </a>
+#### <a href=#awesome-chinese-model-zoo> 🤗 Awesome Chinese Model Zoo </a>
+#### <a href=#industrial-end-to-end-system> 🎛️ Industrial End-to-end System </a>
+#### <a href=#high-performance-distributed-training-and-inference> 🚀 High Performance Distributed Training and Inference </a>
+### Out-of-Box NLP Toolset
+Taskflow aims to provide off-the-shelf NLP pre-built task covering NLU and NLG technique, in the meanwhile with extreamly fast infernece satisfying industrial scenario.
+![taskflow1](https://user-images.githubusercontent.com/11793384/159693816-fda35221-9751-43bb-b05c-7fc77571dd76.gif)
+For more usage please refer to [Taskflow Docs](./docs/model_zoo/taskflow.md).
+### Awesome Chinese Model Zoo
+#### 🀄 Comprehensive Chinese Transformer Models
+We provide **45+** network architectures and over **500+** pretrained models. Not only includes all the SOTA model like ERNIE, PLATO and SKEP released by Baidu, but also integrates most of the high-quality Chinese pretrained model developed by other organizations. Use `AutoModel` API to **⚡SUPER FAST⚡** download pretrained models of different architecture. We welcome all developers to contribute your Transformer models to PaddleNLP!
+```python
+from paddlenlp.transformers import *
+ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+bert = AutoModel.from_pretrained('bert-wwm-chinese')
+albert = AutoModel.from_pretrained('albert-chinese-tiny')
+roberta = AutoModel.from_pretrained('roberta-wwm-ext')
+electra = AutoModel.from_pretrained('chinese-electra-small')
+gpt = AutoModelForPretraining.from_pretrained('gpt-cpm-large-cn')
+```
+Due to the computation limitation, you can use the ERNIE-Tiny light models to accelerate the deployment of pretrained models.
+```python
+# 6L768H
+ernie = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+# 6L384H
+ernie = AutoModel.from_pretrained('ernie-3.0-mini-zh')
+# 4L384H
+ernie = AutoModel.from_pretrained('ernie-3.0-micro-zh')
+# 4L312H
+ernie = AutoModel.from_pretrained('ernie-3.0-nano-zh')
+```
+Unified API experience for NLP task like semantic representation, text classification, sentence matching, sequence labeling, question answering, etc.
+```python
+import paddle
+from paddlenlp.transformers import *
+tokenizer = AutoTokenizer.from_pretrained('ernie-3.0-medium-zh')
+text = tokenizer('natural language processing')
+# Semantic Representation
+model = AutoModel.from_pretrained('ernie-3.0-medium-zh')
+sequence_output, pooled_output = model(input_ids=paddle.to_tensor([text['input_ids']]))
+# Text Classificaiton and Matching
+model = AutoModelForSequenceClassification.from_pretrained('ernie-3.0-medium-zh')
+# Sequence Labeling
+model = AutoModelForTokenClassification.from_pretrained('ernie-3.0-medium-zh')
+# Question Answering
+model = AutoModelForQuestionAnswering.from_pretrained('ernie-3.0-medium-zh')
+```
+#### Wide-range NLP Task Support
+PaddleNLP provides rich examples covering mainstream NLP task to help developers accelerate problem solving. You can find our powerful transformer [Model Zoo](./model_zoo), and wide-range NLP application [exmaples](./examples) with detailed instructions.
+Also you can run our interactive [Notebook tutorial](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/574995) on AI Studio, a powerful platform with **FREE** computing resource.
+<details><summary> PaddleNLP Transformer model summary (<b>click to show details</b>) </summary><div>
+| Model              | Sequence Classification | Token Classification | Question Answering | Text Generation | Multiple Choice |
+| :----------------- | ----------------------- | -------------------- | ------------------ | --------------- | --------------- |
+| ALBERT             | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BART               | ✅                       | ✅                    | ✅                  | ✅               | ❌               |
+| BERT               | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BigBird            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| BlenderBot         | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| ChineseBERT        | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ConvBERT           | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| CTRL               | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| DistilBERT         | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ELECTRA            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| ERNIE              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| ERNIE-CTM          | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| ERNIE-Doc          | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ERNIE-GEN          | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| ERNIE-Gram         | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| ERNIE-M            | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| FNet               | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| Funnel-Transformer | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| GPT                | ✅                       | ✅                    | ❌                  | ✅               | ❌               |
+| LayoutLM           | ✅                       | ✅                    | ❌                  | ❌               | ❌               |
+| LayoutLMv2         | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| LayoutXLM          | ❌                       | ✅                    | ❌                  | ❌               | ❌               |
+| LUKE               | ❌                       | ✅                    | ✅                  | ❌               | ❌               |
+| mBART              | ✅                       | ❌                    | ✅                  | ❌               | ✅               |
+| MegatronBERT       | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| MobileBERT         | ✅                       | ❌                    | ✅                  | ❌               | ❌               |
+| MPNet              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| NEZHA              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| PP-MiniLM          | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| ProphetNet         | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| Reformer           | ✅                       | ❌                    | ✅                  | ❌               | ❌               |
+| RemBERT            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| RoBERTa            | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+| RoFormer           | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| SKEP               | ✅                       | ✅                    | ❌                  | ❌               | ❌               |
+| SqueezeBERT        | ✅                       | ✅                    | ✅                  | ❌               | ❌               |
+| T5                 | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| TinyBERT           | ✅                       | ❌                    | ❌                  | ❌               | ❌               |
+| UnifiedTransformer | ❌                       | ❌                    | ❌                  | ✅               | ❌               |
+| XLNet              | ✅                       | ✅                    | ✅                  | ❌               | ✅               |
+</div></details>
+For more pretrained model usage, please refer to [Transformer API Docs](./docs/model_zoo/index.rst).
+### Industrial End-to-end System
+We provide high value scenarios including information extraction, semantic retrieval, questionn answering high-value.
+For more details industial cases please refer to [Applications](./applications).
+#### 🔍 Neural Search System
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168514909-8817d79a-72c4-4be1-8080-93d1f682bb46.gif" width="400">
+</div>
+For more details please refer to [Neural Search](./applications/neural_search).
+#### ❓ Question Answering System
+We provide question answering pipeline which can support FAQ system, Document-level Visual Question answering system based on [🚀RocketQA](https://github.com/PaddlePaddle/RocketQA).
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168514868-1babe981-c675-4f89-9168-dd0a3eede315.gif" width="400">
+</div>
+For more details please refer to [Question Answering](./applications/question_answering) and [Document VQA](./applications/document_intelligence/doc_vqa).
+#### 💌 Opinion Extraction and Sentiment Analysis
+We build an opinion extraction system for product review and fine-grained sentiment analysis based on [SKEP](https://arxiv.org/abs/2005.05635) Model.
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407260-b7f92800-861c-4207-98f3-2291e0102bbe.png" width="300">
+</div>
+For more details please refer to [Sentiment Analysis](./applications/sentiment_analysis).
+#### 🎙️ Speech Command Analysis
+Integrated ASR Model, Information Extraction, we provide a speech command analysis pipeline that show how to use PaddleNLP and [PaddleSpeech](https://github.com/PaddlePaddle/PaddleSpeech) to solve Speech + NLP real scenarios.
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168412618-04897a47-79c9-4fe7-a054-5dc1f6a1f75c.png" width="500">
+</div>
+For more details please refer to [Speech Command Analysis](./applications/speech_cmd_analysis).
+### High Performance Distributed Training and Inference
+#### ⚡ FastTokenizer: High Performance Text Preprocessing Library
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407921-b4395b1d-44bd-41a0-8c58-923ba2b703ef.png" width="400">
+</div>
+```python
+AutoTokenizer.from_pretrained("ernie-3.0-medium-zh", use_fast=True)
+```
+Set `use_fast=True` to use C++ Tokenizer kernel to achieve 100x faster on text pre-processing. For more usage please refer to [FastTokenizer](./fast_tokenizer).
+#### ⚡ FastGeneration: High Perforance Generation Library
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168407831-914dced0-3a5a-40b8-8a65-ec82bf13e53c.gif" width="400">
+</div>
+```python
+model = GPTLMHeadModel.from_pretrained('gpt-cpm-large-cn')
+outputs, _ = model.generate(
+    input_ids=inputs_ids, max_length=10, decode_strategy='greedy_search',
+    use_fast=True)
+```
+Set `use_fast=True` to achieve 5x speedup for Transformer, GPT, BART, PLATO, UniLM text generation. For more usage please refer to [FastGeneration](./fast_generation).
+#### 🚀 Fleet: 4D Hybrid Distributed Training
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/11793384/168515134-513f13e0-9902-40ef-98fa-528271dcccda.png" width="300">
+</div>
+For more super large-scale model pre-training details please refer to [GPT-3](./examples/language_model/gpt-3).
+## Installation
+### Prerequisites
+* python >= 3.7
+* paddlepaddle >= 2.3
+More information about PaddlePaddle installation please refer to [PaddlePaddle's Website](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/conda/linux-conda.html).
+### Python pip Installation
+```
+pip install --upgrade paddlenlp
+```
+or you can install the latest develop branch code with the following command:
+```shell
+pip install --pre --upgrade paddlenlp -f https://www.paddlepaddle.org.cn/whl/paddlenlp.html
+```
+## Quick Start
+**Taskflow** aims to provide off-the-shelf NLP pre-built task covering NLU and NLG scenario, in the meanwhile with extreamly fast infernece satisfying industrial applications.
+```python
+from paddlenlp import Taskflow
+# Chinese Word Segmentation
+seg = Taskflow("word_segmentation")
+seg("第十四届全运会在西安举办")
+>>> ['第十四届', '全运会', '在', '西安', '举办']
+# POS Tagging
+tag = Taskflow("pos_tagging")
+tag("第十四届全运会在西安举办")
+>>> [('第十四届', 'm'), ('全运会', 'nz'), ('在', 'p'), ('西安', 'LOC'), ('举办', 'v')]
+# Named Entity Recognition
+ner = Taskflow("ner")
+ner("《孤女》是2010年九州出版社出版的小说，作者是余兼羽")
+>>> [('《', 'w'), ('孤女', '作品类_实体'), ('》', 'w'), ('是', '肯定词'), ('2010年', '时间类'), ('九州出版社', '组织机构类'), ('出版', '场景事件'), ('的', '助词'), ('小说', '作品类_概念'), ('，', 'w'), ('作者', '人物类_概念'), ('是', '肯定词'), ('余兼羽', '人物类_实体')]
+# Dependency Parsing
+ddp = Taskflow("dependency_parsing")
+ddp("9月9日上午纳达尔在亚瑟·阿什球场击败俄罗斯球员梅德韦杰夫")
+>>> [{'word': ['9月9日', '上午', '纳达尔', '在', '亚瑟·阿什球场', '击败', '俄罗斯', '球员', '梅德韦杰夫'], 'head': [2, 6, 6, 5, 6, 0, 8, 9, 6], 'deprel': ['ATT', 'ADV', 'SBV', 'MT', 'ADV', 'HED', 'ATT', 'ATT', 'VOB']}]
+# Sentiment Analysis
+senta = Taskflow("sentiment_analysis")
+senta("这个产品用起来真的很流畅，我非常喜欢")
+>>> [{'text': '这个产品用起来真的很流畅，我非常喜欢', 'label': 'positive', 'score': 0.9938690066337585}]
+```
+## API Reference
+- Support [LUGE](https://www.luge.ai/) dataset loading and compatible with Hugging Face [Datasets](https://huggingface.co/datasets). For more details please refer to [Dataset API](https://paddlenlp.readthedocs.io/zh/latest/data_prepare/dataset_list.html).
+- Using Hugging Face style API to load 500+ selected transformer models and download with fast speed. For more information please refer to [Transformers API](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/index.html).
+- One-line of code to load pre-trained word embedding. For more usage please refer to [Embedding API](https://paddlenlp.readthedocs.io/zh/latest/model_zoo/embeddings.html).
+Please find all PaddleNLP API Reference from our [readthedocs](https://paddlenlp.readthedocs.io/).
+## Community
+### Slack
+To connect with other users and contributors, welcome to join our [Slack channel](https://paddlenlp.slack.com/).
+### WeChat
+Scan the QR code below with your Wechat⬇️. You can access to official technical exchange group. Look forward to your participation.
+<div align="center">
+<img src="https://user-images.githubusercontent.com/11793384/212060369-4642d16e-f0ad-4359-aa57-b8303042f9c1.jpg" width="150" height="150" />
+</div>
+## Citation
+If you find PaddleNLP useful in your research, please consider cite
+```
+@misc{=paddlenlp,
+    title={PaddleNLP: An Easy-to-use and High Performance NLP Library},
+    author={PaddleNLP Contributors},
+    howpublished = {\url{https://github.com/PaddlePaddle/PaddleNLP}},
+    year={2021}
+}
+```
+## Acknowledge
+We have borrowed from Hugging Face's [Transformers](https://github.com/huggingface/transformers)🤗 excellent design on pretrained models usage, and we would like to express our gratitude to the authors of Hugging Face and its open source community.
+## License
+PaddleNLP is provided under the [Apache-2.0 License](./LICENSE).
+
+%prep
+%autosetup -n paddlenlp-2.5.2
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-paddlenlp -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 2.5.2-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..f96ed21
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+180cdfcfebfa17d14f5537347a5c0e0f  paddlenlp-2.5.2.tar.gz