Instructions to use fxmarty/tiny-doc-qa-vision-encoder-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fxmarty/tiny-doc-qa-vision-encoder-decoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="fxmarty/tiny-doc-qa-vision-encoder-decoder")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("fxmarty/tiny-doc-qa-vision-encoder-decoder") model = AutoModelForImageTextToText.from_pretrained("fxmarty/tiny-doc-qa-vision-encoder-decoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81fdf01bb2a407a11fb343dde4bfc462730acfa1ec0a22a6e257a2cf5c2637ef
- Size of remote file:
- 15.6 MB
- SHA256:
- a9eb3718c5faad5cd185b54946624ce08596d22a7c28b8be59d49bd5bc8f4912
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