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:
- 71acfe12d46fc8bd440182caab1d68e92d103864ceb8f05fd6d13152f09f28e9
- Size of remote file:
- 3.9 kB
- SHA256:
- 94a37a210c9f86312d2a1c4dfa1a376714d0c73c62be9ac23cd0a267a03d4def
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