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:
- 3e20b4a1050d2808f5487d65b78c0f153296c86784ce8c503d3c018916a3a1df
- Size of remote file:
- 16.2 MB
- SHA256:
- 4535ab25e5e5d1c512dda03fbc18ada42424acd284424c0f4525ab655ccaba87
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