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:
- 774e8a763996c43902dfe519874d06515abd4e7f1dc9eff1bde1d03f6833a37e
- Size of remote file:
- 16.1 MB
- SHA256:
- 5a7781be98498ce94ec5a57ca6a4b6a8199c5cce0e751b6a4567e10d22ea27d4
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