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  1. README.md +7 -9
README.md CHANGED
@@ -7,19 +7,17 @@ metrics:
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  - rouge-l
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  - bertscore
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  - moverscore
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- language: en
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  datasets:
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  - lmqg/qg_zhquad
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  pipeline_tag: text2text-generation
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  tags:
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  - question generation
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  widget:
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- - text: "<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
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  example_title: "Question Generation Example 1"
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- - text: "Beyonce further expanded her acting career, starring as blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac Records."
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  example_title: "Question Generation Example 2"
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- - text: "Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, <hl> Cadillac Records <hl> ."
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- example_title: "Question Generation Example 3"
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  model-index:
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  - name: lmqg/mt5-small-zhquad-qg
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  results:
@@ -54,7 +52,7 @@ This model is fine-tuned version of [google/mt5-small](https://huggingface.co/go
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  ### Overview
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  - **Language model:** [google/mt5-small](https://huggingface.co/google/mt5-small)
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- - **Language:** en
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  - **Training data:** [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) (default)
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  - **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
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  - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
@@ -66,10 +64,10 @@ This model is fine-tuned version of [google/mt5-small](https://huggingface.co/go
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  from lmqg import TransformersQG
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  # initialize model
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- model = TransformersQG(language="en", model="lmqg/mt5-small-zhquad-qg")
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  # model prediction
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- questions = model.generate_q(list_context="William Turner was an English painter who specialised in watercolour landscapes", list_answer="William Turner")
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  ```
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@@ -78,7 +76,7 @@ questions = model.generate_q(list_context="William Turner was an English painter
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  from transformers import pipeline
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  pipe = pipeline("text2text-generation", "lmqg/mt5-small-zhquad-qg")
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- output = pipe("<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.")
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  ```
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  - rouge-l
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  - bertscore
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  - moverscore
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+ language: zh
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  datasets:
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  - lmqg/qg_zhquad
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  pipeline_tag: text2text-generation
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  tags:
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  - question generation
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  widget:
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+ - text: "南安普敦的警察服务由汉普郡警察提供。南安普敦行动的主要基地是一座新的八层专用建筑,造价3000万英镑。该建筑位于南路,2011年启用,靠近<hl> 南安普敦中央 <hl>火车站。此前,南安普顿市中心的行动位于市民中心西翼,但由于设施老化,加上计划在旧警察局和地方法院建造一座新博物馆,因此必须搬迁。在Portswood、Banister Park、Hille和Shirley还有其他警察局,在南安普顿中央火车站还有一个英国交通警察局。"
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  example_title: "Question Generation Example 1"
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+ - text: "芝加哥大学的<hl> 1960—61 <hl>集团理论年汇集了Daniel Gorenstein、John G. Thompson和Walter Feit等团体理论家,奠定了一个合作的基础,借助于其他众多数学家的输入,1982中对所有有限的简单群进行了分类。这个项目的规模超过了以往的数学研究,无论是证明的长度还是研究人员的数量。目前正在进行研究,以简化这一分类的证明。如今,群论仍然是一个非常活跃的数学分支,影响着许多其他领域"
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  example_title: "Question Generation Example 2"
 
 
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  model-index:
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  - name: lmqg/mt5-small-zhquad-qg
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  results:
 
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  ### Overview
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  - **Language model:** [google/mt5-small](https://huggingface.co/google/mt5-small)
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+ - **Language:** zh
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  - **Training data:** [lmqg/qg_zhquad](https://huggingface.co/datasets/lmqg/qg_zhquad) (default)
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  - **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
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  - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
 
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  from lmqg import TransformersQG
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  # initialize model
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+ model = TransformersQG(language="zh", model="lmqg/mt5-small-zhquad-qg")
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  # model prediction
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+ questions = model.generate_q(list_context="南安普敦的警察服务由汉普郡警察提供。南安普敦行动的主要基地是一座新的八层专用建筑,造价3000万英镑。该建筑位于南路,2011年启用,靠近南安普敦中央火车站。此前,南安普顿市中心的行动位于市民中心西翼,但由于设施老化,加上计划在旧警察局和地方法院建造一座新博物馆,因此必须搬迁。在Portswood、Banister Park、Hille和Shirley还有其他警察局,在南安普顿中央火车站还有一个英国交通警察局。", list_answer="南安普敦中央")
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  ```
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  from transformers import pipeline
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  pipe = pipeline("text2text-generation", "lmqg/mt5-small-zhquad-qg")
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+ output = pipe("南安普敦的警察服务由汉普郡警察提供。南安普敦行动的主要基地是一座新的八层专用建筑,造价3000万英镑。该建筑位于南路,2011年启用,靠近<hl> 南安普敦中央 <hl>火车站。此前,南安普顿市中心的行动位于市民中心西翼,但由于设施老化,加上计划在旧警察局和地方法院建造一座新博物馆,因此必须搬迁。在Portswood、Banister Park、Hille和Shirley还有其他警察局,在南安普顿中央火车站还有一个英国交通警察局。")
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  ```
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