Instructions to use hf-internal-testing/tiny-random-MBartModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MBartModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MBartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MBartModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MBartModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a21bcf1d99096b06f3f7b1245e3a7b7a6726d70ebc0743a45a49d3e69d2e8fd5
- Size of remote file:
- 16.1 MB
- SHA256:
- d52c6abb04af6c362db42f530aa203b296d2f23c4389b528c1e4759d4ce1135b
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