Question Answering
Transformers
PyTorch
English
bert
DocVQA
Document Question Answering
Document Visual Question Answering
Instructions to use rubentito/bert-large-mpdocvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rubentito/bert-large-mpdocvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="rubentito/bert-large-mpdocvqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("rubentito/bert-large-mpdocvqa") model = AutoModelForQuestionAnswering.from_pretrained("rubentito/bert-large-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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version https://git-lfs.github.com/spec/v1
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oid sha256:a5dbaee70b76c6a8c833a5f3b328ef065339c98da8440e1063c894ec8d645df0
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size 1336428352
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