Instructions to use hf-internal-testing/tiny-random-ConditionalDetrForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConditionalDetrForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-internal-testing/tiny-random-ConditionalDetrForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ConditionalDetrForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-internal-testing/tiny-random-ConditionalDetrForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5438bade14025cbc30944378a7d97f62b2f4e5ac74eaa53b3502e42c2053216
- Size of remote file:
- 107 MB
- SHA256:
- 40b0653588c3f3b5cd41b9f5d5403c9527b07371d806a56df2af8b98c2128165
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