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:
- 41aa6038db065c0004b4ba5b8ce0e51f0fd816fbf8858d233adaf7f466f56f13
- Size of remote file:
- 3.64 kB
- SHA256:
- f138dd8a50503060f0b971cb02b2acdcb9a3b879591538366a73b258206adc2c
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