Transformers
PyTorch
English
t5
DocVQA
Document Question Answering
Document Visual Question Answering
text-generation-inference
Instructions to use rubentito/hivt5-base-mpdocvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rubentito/hivt5-base-mpdocvqa with Transformers:
# Load model directly from transformers import AutoTokenizer, HiVT5 tokenizer = AutoTokenizer.from_pretrained("rubentito/hivt5-base-mpdocvqa") model = HiVT5.from_pretrained("rubentito/hivt5-base-mpdocvqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b996b5da99dcee708145e5383d9a37754e59ea7136c08507afd9c67c442e04af
- Size of remote file:
- 1.25 GB
- SHA256:
- fb777e6d38088b1221da14e063c65a8da0e6e4b6bcc8b03eeda53268c264f30b
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