Instructions to use hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-tiny-model-private/tiny-random-TableTransformerForObjectDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8f3fe12ab4ecbc3df555bfbf640db909042cdac51ee96fc31e176d0d9f75de7
- Size of remote file:
- 103 MB
- SHA256:
- c30772c57417db9bfa555876155c9a27f760e3f505d4c7e3587dc4a3b673115f
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