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
File size: 134 Bytes
0fcd31e | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:e55e8a5a423b41de28ebb9d5fcc55f1d21d6df7981c1c24afc4725e35c740814
size 265470032
|