Instructions to use google/pix2struct-docvqa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/pix2struct-docvqa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="google/pix2struct-docvqa-base")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("google/pix2struct-docvqa-base") model = AutoModelForImageTextToText.from_pretrained("google/pix2struct-docvqa-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2de80da7079a388b4bd937f7bfbd12240779ed2150c8b67d2d297934263c7219
- Size of remote file:
- 1.13 GB
- SHA256:
- 067f7f314d87fa56daa5bcfaf36fa0b33ceebf7b7d4fae6a1e51ab7af64ee0b5
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