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:
- 0f396023da3ea1ad88d2e7eba8859b7a60adc3dd1e5660c133dc9df83146d45f
- Size of remote file:
- 3.11 MB
- SHA256:
- b228e893d4f5b91819e9452bcab3a571f2f767e0f8e5dba8ca03786e2d3ac9d8
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