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⭐Features

• 📦400+ AI Models: Rich, high-quality AI models, including CV, NLP, Speech, Video and Cross-Modal.
• 🧒Easy to Use: 3 lines of code to predict 400+ AI models.
• 💁Model As Service: Easy to serve model with only one line of command.
• 💻Cross-platform: Support Linux, Windows and MacOS.

💥Recent Updates

• 🔥2022.08.19: The v2.3.0 version is released 🎉

  • Supports ERNIE-ViLG(HuggingFace Space Demo)
  • Supports Disco Diffusion (DD) and Stable Diffusion (SD)

• 2022.02.18: Release models to HuggingFace PaddlePaddle Space

• For more previous release please refer to PaddleHub Release Note

🌈Visualization Demo

🏜️ Text-to-Image Models

👓 Computer Vision Models

• Many thanks to CopyRight@PaddleOCR, PaddleDetection、PaddleGAN, AnimeGAN、openpose、PaddleSeg, Zhengxia Zou、PaddleClas for the pre-trained models, you can try to train your models with them.

🎤 Natural Language Processing Models

• Many thanks to CopyRight@ERNIE、LAC、DDParserfor the pre-trained models, you can try to train your models with them.

🎧 Speech Models

• Many thanks to CopyRight@PaddleSpeech for the pre-trained models, you can try to train your models with PaddleSpeech.

⭐ Thanks for Your Star

• All the above pre-trained models are all open source and free, and the number of models is continuously updated. Welcome Star to pay attention.

🍻Welcome to join PaddleHub technical group

• If you have any questions during the use of the model, you can join the official WeChat group to get more efficient questions and answers, and fully communicate with developers from all walks of life. We look forward to your joining.

• please add WeChat above and send "Hub" to the robot, the robot will invite you to join the group automatically.

✈️QuickStart

🚁The installation of required components.

# install paddlepaddle with gpu
# !pip install --upgrade paddlepaddle-gpu

# or install paddlepaddle with cpu
!pip install --upgrade paddlepaddle

# install paddlehub
!pip install --upgrade paddlehub

🛫The simplest cases of Chinese word segmentation.

import paddlehub as hub

lac = hub.Module(name="lac")
test_text = ["今天是个好天气。"]

results = lac.cut(text=test_text, use_gpu=False, batch_size=1, return_tag=True)
print(results)
#{'word': ['今天', '是', '个', '好天气', '。'], 'tag': ['TIME', 'v', 'q', 'n', 'w']}

🛰️The simplest command of deploying lac service.

!hub serving start -m lac

• 📣More model description, please refer Models List

📚License

The release of this project is certified by the Apache 2.0 license.

👨‍👨‍👧‍👦Contribution

We welcome you to contribute code to PaddleHub, and thank you for your feedback.

• Many thanks to 肖培楷, Contributed to street scene cartoonization, portrait cartoonization, gesture key point recognition, sky replacement, depth estimation, portrait segmentation and other modules
• Many thanks to Austendeng for fixing the SequenceLabelReader
• Many thanks to cclauss optimizing travis-ci check
• Many thanks to 奇想天外，Contributed a demo of mask detection
• Many thanks to mhlwsk，Contributed the repair sequence annotation prediction demo
• Many thanks to zbp-xxxp，Contributed modules for viewing pictures and writing poems
• Many thanks to zbp-xxxp and 七年期限,Jointly contributed to the Mid-Autumn Festival Special Edition Module
• Many thanks to livingbody，Contributed models for style transfer based on PaddleHub's capabilities and Mid-Autumn Festival WeChat Mini Program
• Many thanks to BurrowsWang for fixing Markdown table display problem
• Many thanks to huqi for fixing readme typo
• Many thanks to parano cqvu deehrlic for contributing this feature in PaddleHub
• Many thanks to paopjian for correcting the wrong website address #1424
• Many thanks to Wgm-Inspur for correcting the demo errors in readme, and updating the RNN illustration in the text classification and sequence labeling demo
• Many thanks to zl1271 for fixing serving docs typo
• Many thanks to AK391 for adding the webdemo of UGATIT and deoldify models in Hugging Face spaces
• Many thanks to itegel for fixing quick start docs typo
• Many thanks to AK391 for adding the webdemo of Photo2Cartoon model in Hugging Face spaces