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