Instructions to use jb6692/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jb6692/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="jb6692/test-model")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("jb6692/test-model") model = AutoModelForVisualQuestionAnswering.from_pretrained("jb6692/test-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85bcbffbf2b86b8ba6f4bbec7f63961ae5ede46fbb3a3acc1d17a7d437e32a1b
- Size of remote file:
- 4.66 kB
- SHA256:
- 0d36e581e1dbde4d51c8288d2d008c7e8bb006533c7e266932ed7406854cd8b6
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