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:
- 2b89b1c31d91b25e76c1b3ce2fa8cefcc3b602f596b0789ce4afb700472f7602
- Size of remote file:
- 1.45 MB
- SHA256:
- b01100a9d6f94811c101c57e2cf45cab48d1ce36eaba810c33b3d98ba612cffb
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