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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94f72b3795fd7b4d14a0231adaf74a0da85c03b7b0f35b2416448727a81b8671
- Size of remote file:
- 103 MB
- SHA256:
- 3cf400cf2431a4df81af4a21dd52a3f793aec6714b27ac7a45f68245db40cca3
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