Document Question Answering
Transformers
PyTorch
English
layoutlmv3
DocVQA
Document Question Answering
Document Visual Question Answering
Instructions to use rubentito/layoutlmv3-base-mpdocvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rubentito/layoutlmv3-base-mpdocvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="rubentito/layoutlmv3-base-mpdocvqa")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("rubentito/layoutlmv3-base-mpdocvqa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("rubentito/layoutlmv3-base-mpdocvqa") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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size 503706952
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