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:
- 3e4946a26d4a815673d453259ba94eaa8441a24c6c42092bf01ee3d1394ccd0c
- Size of remote file:
- 408 kB
- SHA256:
- f7c87e1379028b9e975f0811da722f71abd23879a536b140658edde0ad855d85
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