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:
- dc6f6b7fd0db411a12fbfef0b335f84c8f97582ae1df4b5e754970e7b43560e1
- Size of remote file:
- 1.48 MB
- SHA256:
- b6005301157ed0b0aea4b1bd03a99cca6e0b6f76fefe5f00bc23c559a467e8cf
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