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:
- e75337b80141fe9fc1ebdff4a32e844eea2bbbf17718cbf6f6559d9a53bc4eec
- Size of remote file:
- 1.48 MB
- SHA256:
- e69e2bdf27b5fe17d6a32a53dd4a1c34098c8e643db8308a57c9382d829aa7f5
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