Instructions to use hf-internal-testing/tiny-random-PvtV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PvtV2Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-PvtV2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PvtV2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9295b48936ee29768a7158554abadc2f25f21a0143a545638a76d42e5a01418
- Size of remote file:
- 3.11 MB
- SHA256:
- c9a267f48e788e5687d2b6de18f8e27a0c5c04205b0b756049c8bdc4fe5562c9
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