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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52d3105bae89f7bb43e63b939b6cbcf2370163e421280de8e138f82a64bae897
- Size of remote file:
- 1.26 MB
- SHA256:
- 3f3ae0d932e3209a71de11b0bc64dcec7b77a46ebe8e2cb78a4b590f5e6291cd
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