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:
- a78ec2fd0beb7dcb2f507d0142b8b06b385c202293dce1aa37496ea1c97892f5
- Size of remote file:
- 2.67 kB
- SHA256:
- 712ba5cbd109908dcfd55daba9b0c8e0b72f7c1ffefe25ad5d7c8f8b2cefbff5
路
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