Instructions to use teohyc/QwigLip-VQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use teohyc/QwigLip-VQA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="teohyc/QwigLip-VQA")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("teohyc/QwigLip-VQA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b26bd05e7eb82c515b39074705cae59026fded2412cb9658624981c7ddcec90
- Size of remote file:
- 11.4 MB
- SHA256:
- 221e7983f8026485637c40781cee980278901b9965950fb732b43fa438f5c2d5
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