Instructions to use Hellraiser24/vilt-textvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hellraiser24/vilt-textvqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Hellraiser24/vilt-textvqa")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Hellraiser24/vilt-textvqa") model = AutoModelForVisualQuestionAnswering.from_pretrained("Hellraiser24/vilt-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 sha256:80b82c8e73fe2c505edc9a686064971bbcb38c41bfb7d9a4e4a3a88aaa80810b
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size 470379396
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