Instructions to use hf-tiny-model-private/tiny-random-ViltForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ViltForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="hf-tiny-model-private/tiny-random-ViltForQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ViltForQuestionAnswering") model = AutoModelForVisualQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-ViltForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75478d5e83816d5cfda6c4c4b6c18fe5279ba18711ec772c2d21f425d524f734
- Size of remote file:
- 429 kB
- SHA256:
- 5b8a10a1f5794f1881e0441e5972579e67ff8ef2093adaf2ca69f54e0b2ffea3
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