readme: ---
  language: id
  datasets:
  - SQuADv2.0
  tags: 
  - question-generation
  - multitask-model
  - idt5
  widget:
  - text: "generate question: <hl> Dua orang <hl> pengembara berjalan di sepanjang jalan yang berdebu dan tandus di hari yang sangat panas. Tidak lama kemudian, mereka menemukan sebuah pohon besar. </s>"
  - text: "question: Siapa pemimpin Kerajaan Tarumanegara? context: Raja Purnawarman mulai memerintah Kerajaan Tarumanegara pada tahun 395 M. </s>"
      
  license: apache-2.0
  ---
  
  # idT5 for Indonesian Question Generation and Question Answering
  
  [idT5](https://huggingface.co/muchad/idt5-base) (Indonesian version of [mT5](https://huggingface.co/google/mt5-base)) is fine-tuned on 30% of [translated SQuAD v2.0](https://github.com/Wikidepia/indonesian_datasets/tree/master/question-answering/squad) for **Question Generation** and **Question Answering** tasks.
  
  ## Live Demo
  * **Question Generation:** [ai.muchad.com/qg](https://ai.muchad.com/qg/)
  * **Question Answering:** [t.me/caritahubot](https://t.me/caritahubot)
  
  ## Requirements
  ```
  !pip install transformers==4.4.2
  !pip install sentencepiece==0.1.95
  !git clone https://github.com/muchad/qaqg.git
  %cd qaqg/
  ```
  
  ## Usage 🚀
  #### Question Generation
  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/muchad/qaqg/blob/main/idT5_Question_Generation.ipynb)
  
  ```
  from pipeline_qg import pipeline #pipeline_qg.py script in the cloned repo
  qg = pipeline()
  
  #sample
  qg("Raja Purnawarman mulai memerintah Kerajaan Tarumanegara pada tahun 395 M.")
  
  #output
  => [{'answer': 'Raja Purnawarman','question': 'Siapa yang memerintah Kerajaan Tarumanegara?'}, {'answer': '395 M','question': 'Kapan Raja Purnawarman memerintah Kerajaan Tarumanegara?'}]
  ```
  
  
  #### Question Answering
  
  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/muchad/qaqg/blob/main/idT5_Question_Answering.ipynb)
  
  ```
  from pipeline_qa import pipeline #pipeline_qa.py script in the cloned repo
  qa = pipeline()
  
  #sample
  qa({"context":"Raja Purnawarman mulai memerintah Kerajaan Tarumanegara pada tahun 395 M.","question":"Siapa pemimpin Kerajaan Tarumanegara?"})
  
  #output
  => Raja Purnawarman
  ```