Instructions to use ThirdEyeData/Question_Answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThirdEyeData/Question_Answer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ThirdEyeData/Question_Answer")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ThirdEyeData/Question_Answer") model = AutoModelForQuestionAnswering.from_pretrained("ThirdEyeData/Question_Answer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 940e122ae725c12df751008a47289bb04d6951a7f5689be4f41efd50d8b1406f
- Size of remote file:
- 265 MB
- SHA256:
- eb8e4fbac35bd7f8603ede8b042b8deda814aff8d6f575c8fdc867fd5ddcd4b1
路
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