Instructions to use z-uo/roberta-qasper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use z-uo/roberta-qasper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="z-uo/roberta-qasper")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("z-uo/roberta-qasper") model = AutoModelForQuestionAnswering.from_pretrained("z-uo/roberta-qasper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1991db4131718f85413dd28e7ea3b71639d2e7194d1da697f58add7935fc9671
- Size of remote file:
- 496 MB
- SHA256:
- f7f35b01b606756064c3154bc3b7e59a54e2f011aa8ee4425d307be5b1b77b58
路
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