Instructions to use vuiseng9/bert-base-uncased-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vuiseng9/bert-base-uncased-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="vuiseng9/bert-base-uncased-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("vuiseng9/bert-base-uncased-squad") model = AutoModelForQuestionAnswering.from_pretrained("vuiseng9/bert-base-uncased-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3148367e3ab1800c3381c30989324b237de3ebdb2b19c2250a2e899f639e0daf
- Size of remote file:
- 436 MB
- SHA256:
- f48d2ec282a44502b9bbb4c4adb7b9c10f5b043629d24ab1e163d996ba7cbb18
路
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