Instructions to use pardeepSF/layoutlm-vqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pardeepSF/layoutlm-vqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="pardeepSF/layoutlm-vqa")# Load model directly from transformers import AutoTokenizer, AutoModelForDocumentQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("pardeepSF/layoutlm-vqa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("pardeepSF/layoutlm-vqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 386ed3476ed9ef9abf8cfa575253600d7ce44ddeaa4553e23da8eaa4e360fef6
- Size of remote file:
- 1.36 GB
- SHA256:
- 01159ba7af127218df697cc6da8ad1cb8d5b1fa8e8f888e2d4b04623902382e8
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