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:
- 1c8ee4982ceab7cfd2c46afda36a9d23d6185c84e61ea2c01e19aaf38be33821
- Size of remote file:
- 17.1 MB
- SHA256:
- 0df8a0319e6f0464bfac55a5283a8f8ce4a1fb06203fdd2c76ae59c271198e0c
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