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 # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="rubentito/bert-large-mpdocvqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("rubentito/bert-large-mpdocvqa") model = AutoModelForQuestionAnswering.from_pretrained("rubentito/bert-large-mpdocvqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2 opened almost 2 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot