Instructions to use liuliu96/layoutlmv2-base-uncased_finetuned_docvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liuliu96/layoutlmv2-base-uncased_finetuned_docvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="liuliu96/layoutlmv2-base-uncased_finetuned_docvqa")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("liuliu96/layoutlmv2-base-uncased_finetuned_docvqa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("liuliu96/layoutlmv2-base-uncased_finetuned_docvqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9efe6ddae5e3fe27b9d88f61810b54a87861a276735cc4ec9308b2196fb45e08
- Size of remote file:
- 802 MB
- SHA256:
- 80c2aa7719d62b498b6b39b3c3339bf24c370ca0694a3e4650226d184b3cbefd
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