Instructions to use hf-internal-testing/tiny-random-Owlv2ForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Owlv2ForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="hf-internal-testing/tiny-random-Owlv2ForObjectDetection")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Owlv2ForObjectDetection") model = AutoModelForZeroShotObjectDetection.from_pretrained("hf-internal-testing/tiny-random-Owlv2ForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f425061ed4f676bcbc13625bb64e5d25abcd9bfabbdb9e534394e12f87ce1f9f
- Size of remote file:
- 1.53 MB
- SHA256:
- 71cc9bf1a8932dbb037e7fff29c1ed55ffe557db15f864f74c320f58076d59d9
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