Instructions to use MariaK/layoutlmv2-base-uncased_finetuned_docvqa_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MariaK/layoutlmv2-base-uncased_finetuned_docvqa_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="MariaK/layoutlmv2-base-uncased_finetuned_docvqa_v2")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("MariaK/layoutlmv2-base-uncased_finetuned_docvqa_v2") model = AutoModelForDocumentQuestionAnswering.from_pretrained("MariaK/layoutlmv2-base-uncased_finetuned_docvqa_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cec58685249c411d6088fa3d1f4c9991ea9e17d693c4841b5f7a066219d4fe80
- Size of remote file:
- 802 MB
- SHA256:
- 0e29af61a4ac4c424ec6e69089ff6f10b6a72e3bda48b541af48f0480daeb716
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