Instructions to use PrplHrt/LayoutLMv2_hub with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PrplHrt/LayoutLMv2_hub with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="PrplHrt/LayoutLMv2_hub")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("PrplHrt/LayoutLMv2_hub") model = AutoModelForDocumentQuestionAnswering.from_pretrained("PrplHrt/LayoutLMv2_hub") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f7595e4b4e17012ceddfebd6e1af23a8be56b83c38d2b5787a4e98d0283d503
- Size of remote file:
- 802 MB
- SHA256:
- cec033ebbf88a07259ba16a5872ba594a9b3cc1fb95188f80a0e82cc56eb39ec
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