Visual Question Answering
Transformers
Safetensors
Vietnamese
vision-encoder-decoder
image-text-to-text
Instructions to use TeeA/DONUT-ViChart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeeA/DONUT-ViChart with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="TeeA/DONUT-ViChart")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("TeeA/DONUT-ViChart") model = AutoModelForImageTextToText.from_pretrained("TeeA/DONUT-ViChart") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4ba95f56643063dff05245e00315ff9a3c7486bcf6578473b355423871e255c
- Size of remote file:
- 737 MB
- SHA256:
- 7e4b6b129fd0cd6abf2413da95d9d510216bbbf8dca79c909edd6705299daab7
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