Instructions to use VMware/bert-tiny-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/bert-tiny-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/bert-tiny-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/bert-tiny-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/bert-tiny-mrqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb7cc24078d22b81ab78ca4b9a34faa6233f1788ef76b632ffe8ff483505e2c9
- Size of remote file:
- 17.5 MB
- SHA256:
- 88899ca126808885adc74a326383e9d17fb3e56e5dd514f5912be75e13b39936
路
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