Instructions to use madanagrawal/question_answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madanagrawal/question_answering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="madanagrawal/question_answering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("madanagrawal/question_answering") model = AutoModelForQuestionAnswering.from_pretrained("madanagrawal/question_answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ddc1128fbf845092ff65c43ceb21ad8aaab72dc55970290f6bc0be3629e8ab2
- Size of remote file:
- 4.98 kB
- SHA256:
- 050c4bc0583033f47370e561648c57a5a6b207080af8c7a72fc4584f1ed1c614
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