Document Question Answering
Transformers
Safetensors
Vietnamese
vision-encoder-decoder
image-text-to-text
Instructions to use YuukiAsuna/VieTable-donut-docvqa-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YuukiAsuna/VieTable-donut-docvqa-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="YuukiAsuna/VieTable-donut-docvqa-demo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("YuukiAsuna/VieTable-donut-docvqa-demo") model = AutoModelForMultimodalLM.from_pretrained("YuukiAsuna/VieTable-donut-docvqa-demo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from YuukiAsuna/VieTable-donut-docvqa-demo: direct link, hf CLI and curl.
- Browser
- Download file 4.22 MB
-
https://huggingface.co/YuukiAsuna/VieTable-donut-docvqa-demo/resolve/main/tokenizer.json
- Command line
-
hf download hf://YuukiAsuna/VieTable-donut-docvqa-demo/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/YuukiAsuna/VieTable-donut-docvqa-demo/resolve/main/tokenizer.json
4.22 MB
File too large to display, you can check the raw version instead.