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:
- f87bb26c5519451ac01ed0cf46d32f547c0f05afd713c46f6a49604100ceca05
- Size of remote file:
- 1.26 MB
- SHA256:
- 14773daa111a4863004d67f6a536c910b40b5b19f52a0812af008b7e235c1ad9
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