Instructions to use VMware/electra-base-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/electra-base-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/electra-base-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/electra-base-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/electra-base-mrqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a154c76a873e8359ac8696965512f63e1e9aedf3bd22e19053793746fe9a2474
- Size of remote file:
- 436 MB
- SHA256:
- ae30f16a3bd53f1e38969aab92fd202e2e5ae219c7bf0372171fc319ed4c5448
路
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