Instructions to use tiennvcs/layoutlmv2-base-uncased-finetuned-infovqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiennvcs/layoutlmv2-base-uncased-finetuned-infovqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="tiennvcs/layoutlmv2-base-uncased-finetuned-infovqa")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("tiennvcs/layoutlmv2-base-uncased-finetuned-infovqa") model = AutoModelForDocumentQuestionAnswering.from_pretrained("tiennvcs/layoutlmv2-base-uncased-finetuned-infovqa") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#1 opened over 2 years ago
by
SFconvertbot