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:
- f7ecf72be8e8da32d026aa106e4daef222b6a7cf93222d6155200e9be28430f4
- Size of remote file:
- 436 MB
- SHA256:
- 7bee92d3623db2011f8646ff2049b0e8e1a4ede67e25fa58cf6e4d56b896fe95
路
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