Instructions to use hf-tiny-model-private/tiny-random-VisualBertModel 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-VisualBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-VisualBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-VisualBertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-VisualBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8d16e2905e66e660460e1efcf8f3580afc040508d049ab78386c2196ceffed5
- Size of remote file:
- 455 kB
- SHA256:
- 67febf551698d81f607068dc04d822fb829987d3b83de8fad80814721a983b52
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