This model jointly learns all tasks in decaNLP without any task-specific modules or parameters in the multitask setting. Each task is cast as question answering, which makes it possible to use our new Multitask Question Answering Network (MQAN). The Natural Language Decathlon is a multitask challenge that spans ten tasks: question answering (SQuAD), machine translation (IWSLT), summarization (CNN/DM), natural language inference (MNLI), sentiment analysis (SST), semantic role labeling(QA‑SRL), zero-shot relation extraction (QA‑ZRE), goal-oriented dialogue (WOZ, semantic parsing (WikiSQL), and commonsense reasoning (MWSC). At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments.ĭecaNLP - The Natural Language Decathlon: A Multitask Challenge for NLP
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🤗 Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. Its aim is to make cutting-edge NLP easier to use for everyone. 🤗 Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation and more in over 100 languages.
Transformers - 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. You will start with the basics of natural language and Python and move on to advanced analytical and machine learning concepts. A structured and comprehensive approach is followed in this book so that readers with little or no experience do not find themselves overwhelmed.
Learn the techniques related to natural language processing and text analytics, and gain the skills to know which technique is best suited to solve a particular problem.
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Text-analytics-with-python - Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springerĭerive useful insights from your data using Python.
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