Instructions to use badalsahani/oneAPI_QA_Model_kaggle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badalsahani/oneAPI_QA_Model_kaggle with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="badalsahani/oneAPI_QA_Model_kaggle")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("badalsahani/oneAPI_QA_Model_kaggle") model = AutoModelForQuestionAnswering.from_pretrained("badalsahani/oneAPI_QA_Model_kaggle") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93f1edf7616cc32c70e589f4a70b765dba3e586c6ae3d7966ccc27429235d1b6
- Size of remote file:
- 4.03 kB
- SHA256:
- aaa3a2d2df91a66f45734da26ee6a057904688a8ed271a93a9122c83ea31fc8e
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