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PhoBERT: Pre-trained language models for Vietnamese
We present PhoBERT with two versions of "base" and "large"–the first pub...
03/02/2020 ∙ by Dat Quoc Nguyen, et al. ∙
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N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models
We introduce N-LTP, an open-source Python Chinese natural language proce...
09/24/2020 ∙ by Wanxiang Che, et al. ∙
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Transfer Learning Toolkit: Primers and Benchmarks
The transfer learning toolkit wraps the codes of 17 transfer learning mo...
11/20/2019 ∙ by Fuzhen Zhuang, et al. ∙
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Massive Choice, Ample Tasks (MaChAmp):A Toolkit for Multi-task Learning in NLP
Transfer learning, particularly approaches that combine multi-task learn...
05/29/2020 ∙ by Rob van der Goot, et al. ∙
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The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
We present the Language Interpretability Tool (LIT), an open-source plat...
08/12/2020 ∙ by Ian Tenney, et al. ∙
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SciWING – A Software Toolkit for Scientific Document Processing
We introduce SciWING, an open-source software toolkit which provides acc...
04/08/2020 ∙ by Abhinav Ramesh Kashyap, et al. ∙
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Optuna: A Next-generation Hyperparameter Optimization Framework
The purpose of this study is to introduce new design-criteria for next-g...
07/25/2019 ∙ by Takuya Akiba, et al. ∙
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EasyTransfer – A Simple and Scalable Deep Transfer Learning Platform for NLP Applications
11/18/2020 ∙ by Minghui Qiu, et al. ∙
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The literature has witnessed the success of applying deep Transfer Learning (TL) algorithms to many NLP applications, yet it is not easy to build a simple and scalable TL toolkit for this purpose. To bridge this gap, the EasyTransfer platform is designed to make it easy to develop deep TL algorithms for NLP applications. It is built with rich API abstractions, a scalable architecture and comprehensive deep TL algorithms, to make the development of NLP applications easier. To be specific, the build-in data and model parallelism strategy shows to be 4x faster than the default distribution strategy of Tensorflow. EasyTransfer supports the mainstream pre-trained ModelZoo, including Pre-trained Language Models (PLMs) and multi-modality models. It also integrates various SOTA models for mainstream NLP applications in AppZoo, and supports mainstream TL algorithms as well. The toolkit is convenient for users to quickly start model training, evaluation, offline prediction, and online deployment. This system is currently deployed at Alibaba to support a variety of business scenarios, including item recommendation, personalized search, and conversational question answering. Extensive experiments on real-world datasets show that EasyTransfer is suitable for online production with cutting-edge performance. The source code of EasyTransfer is released at Github (https://github.com/alibaba/EasyTransfer).
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