Instructions to use newsha/PQuAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use newsha/PQuAD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="newsha/PQuAD")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("newsha/PQuAD") model = AutoModelForQuestionAnswering.from_pretrained("newsha/PQuAD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7630c97c44288a60dd791bde06f5ebf0b3aff93ec994f028976ccc5854cfc898
- Size of remote file:
- 2.93 kB
- SHA256:
- 46c568a40de24a30413883784a8a9e05bd1d2a2305f081fa27c4d17e77e0f358
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