Instructions to use hf-internal-testing/tiny-random-MobileViTV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileViTV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-MobileViTV2Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MobileViTV2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MobileViTV2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b95612c3020894fab04aa88aa3b521d9dacff2d08e49442aafa522108b2f6c36
- Size of remote file:
- 1.2 MB
- SHA256:
- 1e110624cfd6f9c466587c9908ab12f85c1880b30912c748fb79212ae751bc3b
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