Instructions to use TusharGoel/LayoutLMv2-finetuned-docvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TusharGoel/LayoutLMv2-finetuned-docvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="TusharGoel/LayoutLMv2-finetuned-docvqa")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("TusharGoel/LayoutLMv2-finetuned-docvqa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("TusharGoel/LayoutLMv2-finetuned-docvqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4dd7fc8afeefaf2d2aeabb72625071396cbdc06eb6ded4b82bcd539cc0659566
- Size of remote file:
- 802 MB
- SHA256:
- a2bd729a64b19ca0d2205c21dab3412347c0be7519479ab7bc827861918d30bf
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