readme: ---
  language: pl
  datasets:
  - enelpol/czywiesz
  ---
  
  # Model description
  
  The model was created for selective question answering in Polish. I.e. it is used to find passages containing the answers to the given question.
  
  It is used to encode the contexts (aka passages) in the DPR bi-encoder architecture. The architecture requires two separate models.
  The question part has to be encoded with the corresponding [question encoder](https://huggingface.co/enelpol/czywiesz-question).
  
  The model was created by fine-tuning [Herbert base cased](https://huggingface.co/allegro/herbert-base-cased) on "Czywiesz" dataset. 
  [Czywiesz](https://clarin-pl.eu/dspace/handle/11321/39) dataset contains questions and Wikipedia articles extracted from the Polish Wikipedia.
  
  
  # Usage
  
  It is the easiest to use the model with the [Haystack framework](https://haystack.deepset.ai/overview/intro).
  
  ```python
  from haystack.document_stores import FAISSDocumentStore
  from haystack.retriever import DensePassageRetriever
  
  document_store = FAISSDocumentStore(faiss_index_factory_str="Flat")
  
  retriever = DensePassageRetriever(
      document_store=document_store,
      query_embedding_model="enelpol/czywiesz-question",
      passage_embedding_model="enelpol/czywiesz-context"
  )
  
  for document in documents:
      document_store.write_documents([document])
      
  document_store.update_embeddings(retriever)
  document_store.save("contexts.faiss")
  
  ```