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:
- 9830d31a4a60f67f71f4b6259e33d79df263835acc60c73a5ce714ee838bfec5
- Size of remote file:
- 265 MB
- SHA256:
- e55e8a5a423b41de28ebb9d5fcc55f1d21d6df7981c1c24afc4725e35c740814
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