Instructions to use hf-internal-testing/tiny-random-TableTransformerForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TableTransformerForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-internal-testing/tiny-random-TableTransformerForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-TableTransformerForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-internal-testing/tiny-random-TableTransformerForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 635379501fe27c40c302b7b841aee729969bcd8640654a935bbce34b7ff2ecb0
- Size of remote file:
- 103 MB
- SHA256:
- ea8ecc5aa4e057458041cbcb7aa967c56bc412cb6b4e7792c7d81643e6d6d03d
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