Instructions to use hf-tiny-model-private/tiny-random-MBartModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MBartModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-MBartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MBartModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MBartModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c0a92997693cae86f8802866f33e77210c36c3112a2cd05f75160396046c7a2
- Size of remote file:
- 16.2 MB
- SHA256:
- d1c8b9486e4a64f105c4aaae943d8249ffced169d64ef46974b21b61b8a080d4
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