Instructions to use beneor/layoutlmv2-base-uncased_finetuned_docvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beneor/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="beneor/layoutlmv2-base-uncased_finetuned_docvqa")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("beneor/layoutlmv2-base-uncased_finetuned_docvqa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("beneor/layoutlmv2-base-uncased_finetuned_docvqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2fa66a790a556c6705692d4d5915a5789ac57eaef19bc79f81445f72e8ba209
- Size of remote file:
- 5.3 kB
- SHA256:
- cef5294cfd55824e5d7e410aac280c5611ac29648d7c3570fe75b0ba2482081c
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