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:
- 5d00a6214fa3e9d6ac7b15e7459553f1f3af705f7608e5a47300f5f74a6a08cc
- Size of remote file:
- 16.1 MB
- SHA256:
- ad45fb8a2c03ef25025c3f7358c8c61c982af3fbf06514c6bf13f62d554cfc49
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