Instructions to use PrimWong/layout_qa_hparam_tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PrimWong/layout_qa_hparam_tuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="PrimWong/layout_qa_hparam_tuning")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("PrimWong/layout_qa_hparam_tuning") model = AutoModelForDocumentQuestionAnswering.from_pretrained("PrimWong/layout_qa_hparam_tuning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 514c0d06a011971b5eed18435a918f72ccb2653985467500e87e793ef4140e63
- Size of remote file:
- 802 MB
- SHA256:
- 35db980b48a04ad97bd11f629ef67e1cd1c58aabe4d006a646278bed5975e873
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