Instructions to use hf-internal-testing/tiny-random-TableTransformerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TableTransformerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-TableTransformerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-TableTransformerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-TableTransformerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81d59fd721293a683f98a61d73833b65c2e57c0726e958c3932a7599873b59be
- Size of remote file:
- 103 MB
- SHA256:
- f6dd875ea22624abe28e1cfcec9ac8018af728dda919da61fc3a485843a18549
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