Instructions to use VMware/electra-large-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/electra-large-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/electra-large-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/electra-large-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/electra-large-mrqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d14c257ae320a02e0dd78afc10f0dc60957ccb58b52468d74c24f9ed504b5904
- Size of remote file:
- 1.34 GB
- SHA256:
- 159a10cd8a910f6f7245e4bdb03bf82a61bd2d87bc7e6e26d16ace95ab8b5afa
路
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