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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f65fe6d4258295c1393feddba5453a428d74755b0f87f6f7b6d213228d469ac1
- Size of remote file:
- 54 MB
- SHA256:
- 97e5a592825705a83332742df51014f66148882a55d2aa70b92eafd551824ec1
路
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