Transformers
PyTorch
English
t5
DocVQA
Document Question Answering
Document Visual Question Answering
text-generation-inference
Instructions to use rubentito/vt5-base-spdocvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rubentito/vt5-base-spdocvqa with Transformers:
# Load model directly from transformers import AutoTokenizer, HF_VT5 tokenizer = AutoTokenizer.from_pretrained("rubentito/vt5-base-spdocvqa") model = HF_VT5.from_pretrained("rubentito/vt5-base-spdocvqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c0d5fdc02408d7f9975b780216763c92ebd711410caab76d901bfef97980c3b
- Size of remote file:
- 1.25 GB
- SHA256:
- f046648f7f4ede1984c33f8d596871a53b60606d9b600917b9fb11e5733bef86
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