Instructions to use AmazonScience/qanlu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmazonScience/qanlu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="AmazonScience/qanlu")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("AmazonScience/qanlu") model = AutoModelForQuestionAnswering.from_pretrained("AmazonScience/qanlu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a00608610561fc844b24115c790cda8868aabcac12b0428dc956f5233285f69
- Size of remote file:
- 1.71 kB
- SHA256:
- 741ea32a9367dd79ceb565c8d97973393806411e229e01889ce49fd47a0d63de
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