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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e55e8a5a423b41de28ebb9d5fcc55f1d21d6df7981c1c24afc4725e35c740814
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size 265470032
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