Instructions to use microsoft/git-large-textvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/git-large-textvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="microsoft/git-large-textvqa")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("microsoft/git-large-textvqa") model = AutoModelForImageTextToText.from_pretrained("microsoft/git-large-textvqa") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d282bfbc30587804801e7714a84cad87b1010b1311cb562680b41ac7c25dd72e
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size 1579504880
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