Instructions to use Bingsu/temp_vilt_vqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bingsu/temp_vilt_vqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Bingsu/temp_vilt_vqa")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Bingsu/temp_vilt_vqa") model = AutoModelForVisualQuestionAnswering.from_pretrained("Bingsu/temp_vilt_vqa") - 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 sha256:46a0eebcb3aa7b6723ec2f76668efba9445e55dcd4a80925ec384c2f182d1e04
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size 539483392
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