Instructions to use Sharka/CIVQA_DVQA_LayoutXLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharka/CIVQA_DVQA_LayoutXLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="Sharka/CIVQA_DVQA_LayoutXLM")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("Sharka/CIVQA_DVQA_LayoutXLM") model = AutoModelForDocumentQuestionAnswering.from_pretrained("Sharka/CIVQA_DVQA_LayoutXLM") - Notebooks
- Google Colab
- Kaggle
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You can find more information about this
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You can find more information about this model in this [paper](https://nlp.fi.muni.cz/raslan/raslan23.pdf#page=31).
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