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:
- 4d14daf5f1d8b24ed10b6b615ae507e6dd5084c34508b12f083f1f57019283f8
- Size of remote file:
- 3.11 MB
- SHA256:
- fbe29d9eb22065b36814df43fd6b6c1fed5ba4dd92042ef4d865919dba2080fc
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