Instructions to use hf-tiny-model-private/tiny-random-TableTransformerModel 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-TableTransformerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-TableTransformerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-TableTransformerModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-TableTransformerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58a4137f31a85954fee84453e001ebfff94ae4bc2acedf79e4bd9b2be423080d
- Size of remote file:
- 103 MB
- SHA256:
- 889342b82b9a8de36a1f28f5664425c04f55890f424a1998ff78fd0e540e78a5
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