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:
- 5d9df70894feb7c90ab6863636030e4993418259d6c4d28ee6d8dae574f62c7c
- Size of remote file:
- 3.58 kB
- SHA256:
- 728a47664442705434c773262c7c49766c11bcf41e1d1c86e4be721cc2f21389
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