Instructions to use z-uo/bert-qasper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use z-uo/bert-qasper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="z-uo/bert-qasper")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("z-uo/bert-qasper") model = AutoModelForQuestionAnswering.from_pretrained("z-uo/bert-qasper") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d53960f08993b599a9699995d8b3a75f6cc64f244f6cdf65b1adfe3f6774a4c8
- Size of remote file:
- 436 MB
- SHA256:
- 7d02414120f6ef11123bdffbf89aa4379081a63edc2746219a0b4a1971cd0240
路
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