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:
- 72f9891e2f726eb669562d0876291ca9fa952cd87332e4127ecac248fa1f7943
- Size of remote file:
- 3.06 kB
- SHA256:
- 118ec39ea2e76b66932593128fa5d7ebd4b0960faba102cea89d50533bc9404e
路
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