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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1de4309fbc8c700d6fa52ac14ed108609d25fefdb80dddb3d107ed76b5728000
- Size of remote file:
- 1.36 GB
- SHA256:
- cfc74f8966780254bf142a3eb13696b432812aa8fffbaa21340460090b8c51c2
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