Instructions to use rezabarati/my_awesome_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rezabarati/my_awesome_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="rezabarati/my_awesome_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("rezabarati/my_awesome_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("rezabarati/my_awesome_qa_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9587a559002ad1d262d263e52b5b5e983debcb2e637638a70d3a531aa7ec8439
- Size of remote file:
- 266 MB
- SHA256:
- c07a818e026883180a465e65e18080cc1d6d9f22e5a3738e46738e4b58e8e90e
路
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