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:
- 4c3eda39dc924c42ac862e9987aeb3d3e4a666a1239461cd60d6cc9fb78a46d4
- Size of remote file:
- 16.1 MB
- SHA256:
- 7a7f2a1232bfd74d91598d0fa6056dc73eed2a66516bcbf076b6b20ca80e7fa6
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