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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d71a7fcd653af54a0a15ef4e02429415b0d658d70dcfc188eabb3bffadcf3da2
- Size of remote file:
- 16.2 MB
- SHA256:
- ffbe28c8783428077670edef0bd004e2cfe041f05aaeecfbf6c2421386827905
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