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:
- 45742218d68a63667b637bc79698565977a98b3138e70ea80addb7242fa2ae9f
- Size of remote file:
- 649 MB
- SHA256:
- acba6371874ab1b7cd69282bc2bf7c439c2c176a8ebafbc2f6d4389681568c87
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