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:
- 49a77b255fa665a6b1c664657b6c68cd5f24d51c163a330d8256e0d7412c9996
- Size of remote file:
- 16.1 MB
- SHA256:
- eb9f357ca4a6733884a070145f8d481338075dc65d5badc989ec1bc74491c191
路
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