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:
- 87222836c0952e188c0646fffa447d98996e50161ca6253b38b21d242c486b03
- Size of remote file:
- 1.26 MB
- SHA256:
- bc888211d6a240773d5711020a6f606cc5fd1f1727f8776df09c57685c919073
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