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:
- d2b383ba2ee69a2d4cc3d155c9c9aa3cc01df8edff482c01002403810b078c8c
- Size of remote file:
- 1.45 MB
- SHA256:
- 6b37b44d58a9b69bca2b27bd9d1f37fa878c2983d9c190b434e490e6a10bf4b6
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