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
File size: 441 Bytes
ccfda19 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"do_align_long_axis": false,
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": true,
"do_thumbnail": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "DonutImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"processor_class": "DonutProcessor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 2560,
"width": 1920
}
}
|