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title: README |
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emoji: 📊 |
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colorFrom: blue |
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colorTo: pink |
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sdk: static |
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pinned: false |
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--- |
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<p align="center"> |
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<img src="https://raw.githubusercontent.com/asahi417/lm-question-generation/master/assets/example.png" width="900"> |
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</p> |
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<br> |
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***Language Models for Question Generation (LMQG)*** is the official registry of <a href="https://aclanthology.org/2022.emnlp-main.42/">"Generative Language Models for Paragraph-Level Question Generation, EMNLP 2022"</a>, which has proposed <a href="https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md">QG-Bench</a>, multilingual and multidomain question generation datasets and models. |
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See the official <a href="https://github.com/asahi417/lm-question-generation">GitHub</a> for more information. |
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The QG models can be used with <a href="https://pypi.org/project/lmqg">`lmqg`</a> library as below. |
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<pre class="line-numbers"> |
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<code class="language-python"> |
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from lmqg import TransformersQG |
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model = TransformersQG(language='en', model='lmqg/t5-large-squad-qg-ae') |
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context = "William Turner was an English painter who specialised " |
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"in watercolour landscapes. He is often known as " |
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"William Turner of Oxford or just Turner of Oxford to " |
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"distinguish him from his contemporary, J. M. W. Turner. " |
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"Many of Turner's paintings depicted the countryside " |
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"around Oxford. One of his best known pictures is a " |
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"view of the city of Oxford from Hinksey Hill." |
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question_answer = model.generate_qa(context) |
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print(question_answer) |
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[ |
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('Who was an English painter who specialised in watercolour landscapes?', |
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'William Turner'), |
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("What was William Turner's nickname?", |
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'William Turner of Oxford'), |
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("What did many of Turner's paintings depict around Oxford?", |
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'countryside'), |
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("What is one of William Turner's best known paintings?", |
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'a view of the city of Oxford') |
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] |
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</code> |
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</pre> |
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See more information bellow. |
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<ul> |
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<li> lmqg: <a href="https://github.com/asahi417/lm-question-generation">https://github.com/asahi417/lm-question-generation</a></li> |
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<li> QG-Bench: <a href="https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets">https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets</a></li> |
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<li> Paper (EMNLP 2022): <a href="https://aclanthology.org/2022.emnlp-main.42/">https://aclanthology.org/2022.emnlp-main.42/</a></li> |
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</ul> |
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