Instructions to use xhyi/layoutlmv3_docvqa_t11c5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xhyi/layoutlmv3_docvqa_t11c5000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="xhyi/layoutlmv3_docvqa_t11c5000")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("xhyi/layoutlmv3_docvqa_t11c5000") model = AutoModelForDocumentQuestionAnswering.from_pretrained("xhyi/layoutlmv3_docvqa_t11c5000") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
LayoutLMv3: DocVQA Replication WIP
See experiments code: https://github.com/redthing1/layoutlm_experiments
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