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:
- b04b3b67f6e27aebbcc5af0a2333376fe91405b66698a0460bf5404d667a2584
- Size of remote file:
- 1.45 MB
- SHA256:
- e27304cba2dac1ce5c310b50b49272997e58a0828d2a3759d84a94e59b63205d
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