Instructions to use hf-internal-testing/tiny-vilt-random-vqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-vilt-random-vqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="hf-internal-testing/tiny-vilt-random-vqa")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-vilt-random-vqa") model = AutoModelForVisualQuestionAnswering.from_pretrained("hf-internal-testing/tiny-vilt-random-vqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9da8f45f8da20a4988fa704209dce25d345b65659d9214f12ebb400e0056745c
- Size of remote file:
- 2.61 MB
- SHA256:
- 4da7d508e0c4779e93ea5132fc7bcaf912f38229a3ec134490aca55e1e16e4d3
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