Instructions to use arampacha/electra-base-inqg-span with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arampacha/electra-base-inqg-span with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="arampacha/electra-base-inqg-span")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("arampacha/electra-base-inqg-span") model = AutoModelForQuestionAnswering.from_pretrained("arampacha/electra-base-inqg-span") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8881c8b30d9d2a398f28ed64e7527acbd683eb75402265264678d03bc2feaf5
- Size of remote file:
- 3.06 kB
- SHA256:
- f4b4e85c86b6d88ad475b90c0fa2bec0ec839663adf4d02489f90cde66b9bb12
路
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