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:
- a48a9a368acec3f0b31ada3f6cbd63f06aba0483733c0a9a34d4565061bc46d7
- Size of remote file:
- 103 MB
- SHA256:
- 43116e837b489f187822c594900632733a0a474acd55bdb0762ee7fe6815c5b8
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