Instructions to use google/pix2struct-ocrvqa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/pix2struct-ocrvqa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="google/pix2struct-ocrvqa-base")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("google/pix2struct-ocrvqa-base") model = AutoModelForImageTextToText.from_pretrained("google/pix2struct-ocrvqa-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e980f1b6f13bd491df529881ee0c06b130801fd8725c6281ef003994f67d6643
- Size of remote file:
- 1.13 GB
- SHA256:
- ccc3bcc012dd26afd301468eb10add664ecc06b30035f318274edd75074c8c32
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.