Instructions to use hf-internal-testing/tiny-random-VisualBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VisualBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-VisualBertModel")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-VisualBertModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-VisualBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd922d5e0a7b27899ba83e20b3a3318cd610153ddbbb25d8cab69f775d23d596
- Size of remote file:
- 455 kB
- SHA256:
- 6581630411fa386c49e6afc114f3a1e0f2180917de397957c24f99dfacbc62c7
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