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, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-VisualBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-VisualBertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91a09a604b53da1f6ec2611f4c786dfde0fbca8b667769158207f80adf9b0168
- Size of remote file:
- 436 kB
- SHA256:
- 27643c6c3db3742b7b08b61d007556e736c5cf8943f6d0b7beef63b218696c97
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