Instructions to use hf-tiny-model-private/tiny-random-MBartForQuestionAnswering 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-MBartForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-MBartForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MBartForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MBartForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8c6ba2dc058ff8b535e15315d046fd8921fa156c8a4965890ed83fab8bc651b
- Size of remote file:
- 16.1 MB
- SHA256:
- 0de052a6d35bc077210945ac8aa9a38cc71d980b9162b793e4646e0ac9a20b05
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