Instructions to use VMware/electra-small-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/electra-small-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/electra-small-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/electra-small-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/electra-small-mrqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22528caa330ff644dc4f80766c2014673077ade445846129099a87993d5b5c18
- Size of remote file:
- 54 MB
- SHA256:
- a0fae75b472b14552079007996293b6f0d9916060b25c43979f664f353a14298
路
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