Instructions to use hf-internal-testing/tiny-random-Owlv2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Owlv2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Owlv2Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Owlv2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Owlv2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f422470e850531b8d12b459fd95af91cf50a54f79b6d65c187dae0ed3254b675
- Size of remote file:
- 1.5 MB
- SHA256:
- 08a251d760a557c8eeb869793cf0dc97709f63157e8c66db79d614237f5433f6
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